Miracle-dz/UniFAR-FTUs huggingface dataset:
HYPOTHESIS GENERATION FOR RARE AND UNDIAGNOSED DISEASES THROUGH CLUSTERING AND CLASSIFYING TIME-VERSIONED BIOLOGICAL ONTOLOGIES

Rare diseases affect 1-in-10 people in the United States and despite increased genetic testing, up to half never receive a diagnosis. Even when using advanced genome sequencing platforms to discover variants, if there is no connection between the variants found in the patient’s genome and their phe-notypes in the literature, then the patient will remain undiagnosed. When a direct variant-phenotype connection is not known, putting a patient’s information in the larger context of phenotype relation-ships and protein-protein-interactions may provide an opportunity to find an indirect explanation. Databases such as STRING contain millions of protein-protein-interactions and HPO contains the relations of thousands of phenotypes. By integrating these networks and clustering the entities within we can potentially discover latent gene-to-phenotype connections. The historical records for STRING and HPO provide a unique opportunity to create a network time series for evaluating the cluster sig-nificance. Most excitingly, working with Children’s Hospital Colorado we provide promising hy-potheses about latent gene-to-phenotype connections for 38 patients with undiagnosed diseases. We also provide potential answers for 14 patients listed on MyGene2. Clusters our tool finds significant harbor 2.35 to 8.72 times as many gene-to-phenotypes edges inferred from known drug interactions than clusters find to be insignificant. Our tool, BOCC, is available as a web app and command line tool.
Genetically stable kill-switch using “demon and angel” expression construct of essential genes

Genetic instability of synthetic genetic devices is a key obstacle for practical use. This problem is particularly critical in kill-switches for conditional host killing. Here, we propose a genetically stable kill-switch based on a “demon and angel” expression construct of a toxic essential gene. The kill-switch conditionally overexpresses the toxic essential gene. Additionally, the identical essential gene is deleted in the genome. The essential gene is expressed at a low level to maintain host survival in the OFF state and kills the host by the overexpression in the ON state. The single expression construct is responsible for both killing the hosts and maintaining viability, reducing the emergence of loss-of-function mutants. We constructed the kill-switch using the toxic essential gene encoding tyrosyl-tRNA synthetase, tyrS, in Escherichia coli. The bacteria harboring the kill-switch were conditionally suicidal over 300 generations. Toxic overexpression of essential genes has also been found in other organisms, suggesting that the “demon and angel” kill switch is scalable to various organisms. GRAPHICAL ABSTRACT
Mark-Recapture Abundance Estimate of Fall-Run Chum Salmon in the Upper Tanana River, Alaska, 1995

The primary objective of this study was to determine the feasibility of a mark-recapture program to estimate inseason and postseason abundance of fall-run chum salmon Oncorhynchus keta in the upper Tanana River. We used 2 fish wheels, each on opposite riverbanks, to capture fish for tagging and 2 additional fish wheels on opposite riverbanks to recover tagged fish approximately 76 km upstream. All chum salmon caught during a daily 6-h schedule were marked with spaghetti tags. From 16 August through 30 September 1995, a total of 3,993 fall-run chum salmon were released with orange tags from the right bank; 181 were released with yellow tags from the left bank. From 18August to 1 October, the right-bank recovery wheel caught 6,773 chum salmon, of which 103 were recaptures (94 orange; 9 yellow). During the same period, the left-bank recovery wheel caught 3,902 chum salmon, of which 63 were recaptures (55 orange; 8 yellow). Catches from both recovery wheels were pooled be­ cause tagged fish were not bank-oriented and there was no statistically significant difference in the marked propor­ tions between each wheel. However, information from yellow-tagged fish was not adequate for estimating abun­ dance. Bailey’s closed population model produced a total estimate of 268,173 (SE = 21,597) fall-run chum salmon that passed the tagging site after 16 August. No significant sources of bias from assumption violations were de­ tected. The mean migration rate between tagging and recovery sites was 26 km/d. We concluded that a markrecapture program using fish wheels for fish capture appears feasible but should continue in a developmental stage to allow further evaluation of its utility under a variety of circumstances. Tagging fish from only the right-bank tagging wheel and tagging more fish, while using 2 wheels for tag recovery, may be necessary to improve precision of the abundance estimate.
All outputs in CentAUR are protected by Intellectual Property

A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show largescale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in C.
All outputs in CentAUR are protected by Intellectual Property

Mamais, A. , Chia, R. , Beilina, A. , Hauser, D. N. , Hall, C. , Lewis, P. A. , Cookson, M. R. and Bandopadhyay, R. (2014) Arsenite stress down­regulates phosphorylation and 14­3­3 binding of leucine­rich repeat kinase 2 (LRRK2), promoting self­association and cellular redistribution. Journal of biological chemistry, 289 (31). pp. 21386­21400. ISSN 1083­ 351X doi: https://doi.org/10.1074/jbc.M113. 528463 Available at http://centaur.reading. ac.uk/77591/
Programmatic Strategy Synthesis: Resolving Nondeterminism in Probabilistic Programs

We consider imperative programs that involve both randomization and pure nondeterminism. The central question is how to find a strategy resolving the pure nondeterminism such that the so-obtained determinized program satisfies a given quantitative specification, i.e., bounds on expected outcomes such as the expected final value of a program variable or the probability to terminate in a given set of states. We show how memoryless and deterministic (MD) strategies can be obtained in a semi-automatic fashion using deductive verification techniques. For loop-free programs, the MD strategies resulting from our weakest precondition-style framework are correct by construction. This extends to loopy programs, provided the loops are equipped with suitable loop invariants - just like in program verification. We show how our technique relates to the well-studied problem of obtaining strategies in countably infinite Markov decision processes with reachability-reward objectives. Finally, we apply our technique to several case studies.
Network-based robust H ∞ control of systemswith uncertainty

This paper is concerned with the design of robust H∞ controllers for uncertain networked control systems (NCSs) with the effects of both the network-induced delay and data dropout taken into consideration. A new analysis method for H∞ performance of NCSs is provided by introducing some slack matrix variables and employing the information of the lower bound of the network-induced delay. The designedH∞ controller is of memoryless type, which can be obtained by solving a set of linear matrix inequalities. Numerical examples and simulation results are given finally to illustrate the effectiveness of the method. 2005 Elsevier Ltd. All rights reserved.
Numerical simulation of stick-slip behaviours of typical faults in biaxial compression based on a frictional-hardening and frictional-softening model

S U M M A R Y Stick-slip behaviours of typical faults and interactions among faults are numerically modelled using a proposed frictional-hardening and frictional-softening elastoplastic continuum model. Forty numerical tests in biaxial compression are conducted quasi-statically or dynamically in plane strain and in small or large strain mode using FLAC-3D. Faults are modelled by square or quadrilateral elements from a viewing angle perpendicular to the maximum surface of a specimen. An incremental plastic shear strain in a stick-slip cycle is involved in the model, which is calculated at the beginning of slip and then is set to be zero upon reaching its maximum at the end of stick. Thus, the repeated stick-slip behaviour can be modelled using the same set of equations, and only the evolution of an internal frictional angle is required to be different at different stages. At the slip stage, a decrease of the angle leads to an increase of the incremental plastic shear strain, while at the following stick stage, it is updated according to the present incremental plastic shear strain. Nodal velocities change at the two stages because of the use of dynamic equations even though a rateand state-dependent law is not introduced. Effects of loading rate, fault width and maximum incremental plastic shear strain are investigated. To obtain size-independent stress-deformation curves, a slower loading is required for a finer mesh to ensure the same propagating distance of stress wave. For two intersecting faults or an echelon fault, a few small events are observed at the stick stage because of interactions among faults, whereas only one large event is observed at the slip stage. For a specimen with a bending fault, as the angle between two fault segments is large, the asynchronic softening and hardening of fault elements lead to a small stress drop at loading ends (stable sliding) rather than a saw-tooth-like behaviour (stick-slip). To validate the proposed model, a laboratory test is modelled quasi-statically that was performed on a specimen including an inclined fault oriented an angle of 60◦ with the horizontal direction in biaxial compression. The physical and numerical results agree well. Numerical results show that the stick-slip period is doubled if the loading velocity is halved. Compared with the rateand state-dependent law, the present model is simple and can be implemented in FLAC-3D, capable of modelling the effects of creep, seepage and temperature. For complex faults under complex loading conditions, the proposed model can be used to identify faults prone to sliding or those with large stress drops, and to investigate active sequences of faults and their interactions. Advantages and disadvantages of square or quadrilateral meshes are also addressed, especially on the aspect of stick-slip modelling. For a bending or a single straight fault, a long stick-slip period and a low load-carrying capacity are obtained for quadrilateral meshes, but not for square meshes.
Optimal resource allocation for data service in CDMA reverse link

The optimal resource allocation policy is studied in this paper, for nonreal-time users in CDMA reverse link. The resource allocation policy of interest includes channel coding, spreading gain control and power allocation under the conventional receiver operation-multiuser detection technique is not considered. The constraints in the optimization include peak transmit power of the mobile station, total received power at the base station and QoS in the form of minimum SINR for each user. The coding and spreading gain control can be separated from the power allocation strategy. Our results show that the optimal power allocation policy depends on the objective function: to maximize the sum of throughput from each user, a greedy policy is optimal where the good users (mobile stations with good radio conditions) transmit with full power, bad users (mobile stations with poor radio conditions) barely achieve their QoS and there is at most one user in-between; on the other hand, to maximize the product of throughput from each user, a fair policy is optimal where the bad users transmit with full power and the good users transmit with powers to reach a common received power level. The fairness of the optimal policy in the latter case makes QoS constraint unnecessary. Furthermore, we have found a unified approach in deriving these optimal policies. This approach can also be applied to other power allocation problems in CDMA reverse link. We also present numerical results on the channel capacity under both objectives and the effect of QoS constraint.
Exploring GeoAI Methods for Supraglacial Lake Mapping on Greenland Ice Sheet

The ACM SIGSPATIAL Cup 2023 proposed the challenge to identify and map supraglacial lakes in Greenland in satellite imagery. The peculiarities of supraglacial lakes pose a hard problem for semantic segmentation and object detection tasks because the definition of a lake is ill-fitted to the inner workings of such approaches. For example, lakes are often covered by ice and snow and narrow streams can connect distinct lakes, which is not directly translatable to the semantic segmentation of water. It is also not well-posed for object detection, especially the identity relation - what is a lake, what is not (yet) a lake, and what are two lakes is challenging. In this context, we worked on adapting semantic segmentation using the Segment Anything Model and instance segmentation using Mask R-CNN to the setting. The latter ended up superior in our own evaluation and even got ranked second among all participants. We are proud that our approach has led to competitive performance. The source code is available from https://github.com/tum-bgd/GISCup23.
Representing First-order Problems for Heuristic Selection

Machine learning (ML) has been applied to Automated Theorem Provers (ATPs) with much success in recent years. However, representing ﬁrst-order problems effectively as feature vectors remains a major challenge. The performance of an ML approach is bounded by how well the features represent the problems and relates to the task at hand. In this paper, we investigate the effectiveness of different problem representations for heuristic selection embeddings
EXPERIMENTAL STUDY OF STRENGTH DEGRADATION LAW OF SURROUNDING ROCK IN FRACTURED ZONE OF DEEP ROADWAY

In order to study the strength degradation law of surrounding rock in fractured zone of deep roadway,the loading-unloading tests on intact sandy mudstone samples were implemented according to the stress path simulating the changing law of stress in fractured zone of roadway by applying the MTS815 servo-controlled rock mechanics testing machine.The initial damaged rock samples for different broken levels were obtained and their triaxial strength characters under varying confining pressures were tested with single block method.The strength degradation ratio and volume expansion ratio DV were applied as damage valuables at unloading point;and the function relationships between peak strength,strength parameters of initial damaged rock samples and,DV were established.The study results indicate that the peak strength,cohesion and internal friction angle decrease greatly with the increasing broken level in exponential degradation law.
FREQUENCY AUGMENTED CLOCK SYNCHRONIZATION FOR SPACE-BASED INTERFEROMETRY

Recently, an increase in distributed space systems and a rise in number of nodes in such systems is observed in numerous space applications, for example space-based interferometry. Such applications pose stringent demands on time synchronization which can be challenging to achieve for satellite networks that lack an absolute time reference source, as would be the case with networks beyond Earth orbit. In this paper, we propose a new class of frequency-based and multi-domain time synchronization and ranging algorithms applicable to anchorless mobile networks of asynchronous nodes. First, the Frequency-based Pairwise Least Squares (FPLS) that estimates clock skew and relative velocity under constant pairwise velocity assumption. Second, the Combined Pairwise Least Squares (CPLS) — a two step approach where first, skew and velocity are estimated using FPLS and then its results are fed into a reformulated time domain method to estimate offset and range. The proposed methods are applied to a case study to OLFAR — a spaceborne large aperture radio interferometric array platform for observing the cosmos in the frequency range from 0.3 MHz to 30 MHz to be stationed in the Lunar orbit. The results show that the proposed methods decrease communication and computation needs and can improve the clock synchronization performance for space-based interferometry.
Satellite Dataset Visual Analysis for Remote Soil Nutrient Estimation

This paper proposes a methodology for visualizing satellite-based machine learning (ML) datasets to understand the visual components that will be used as inputs for developing ML models. The proposed methodology uses t-Distributed Stochastic Neighbor Embedding (T-SNE) methods to create visualizations of satellite images leveraging models that were pre-trained in ImageNet. T-SNE is a self-supervised learning tool used to transform high-dimensional spaces into two-or three-dimension embeddings, making it easier to visualize a broad dataset in a single image or space. The methodology is demonstrated using the LUCAS Topsoil Analysis dataset with satellite images from Sentinel-2. The dataset was constructed using the TerraSense Toolkit (TSTK). The T-SNE visualization tool aims to improve ML research by providing a clearer visual understanding of satellite-based datasets.
Prototype Infrastructure for Autonomous On-board Conjunction Assessment and Collision Avoidance

We are working to build a prototype infrastructure for scalable autonomous conjunction assessment and avoidance. This includes a ground hub to synchronize state information and planed maneuvers from operators and identify potential conjunctions, and on-board flight software for autonomous assessment and avoidance of collisions. This work will be flown as part of a NASA STMD flight experiment in 2023
A Software Execution Data Component Identification Algorithm Based on Spectral Clustering

In order to understand the architecture of software system and facilitate the future maintenance of the software, we can reconstruct the software system as a component-based software system. To obtain the component information of the software, it is necessary to identify components based on the information contained in the software execution data. This paper presents a Software Execution data component identification algorithm based on Spectral Clustering (SESC). The input of the algorithm is the software execution event log, and the output is an evaluation report on the quality of the identified components, yielding the log of software execution events with component information. By using four software execution event logs, we compare the proposed SESC with five component identification algorithms based on the community detection algorithm. SESC takes the number of calls between classes into consideration, so it can identify components more accurately, and has certain advantages in time performance.
The calculation of the Sectionalizer location in Medium Voltage Distribution Systems to reduction the Expected Energy Not-Supplied to consumer

An approach is proposed that allows you to quickly and accurately calculate the optimal location for installing a sectionalizing device in power distribution networks with a tree structure. This approach is adopted to medium voltage distribution network with one power source and one main vacuum circuit breaker. Also are analyzed systems that can automatically switch the load to an alternate external grid and have secondary circuit breaker that is normal off. The objective function for calculating the sectionalizer location is to reduce value of the expected energy not-supplied to the consumers in a case installation one sectionalizer. The results of solving objective function are summarized in tabular forms. This result is easy to use during approximate calculations. To improve accuracy, an algorithm for solving a discrete problem is proposed, which uses an approximate result obtained in a tabular manner to reduce the complexity of calculations.
Rare Heart Transplant Rejection Classification Using Diffusion-Based Synthetic Image Augmentation

Heart Transplant Rejection (HTR) is a rare condition that requires early detection to prevent lasting damage to the transplanted heart. Unfortunately, the current HTR grading through biopsy image classification lacks consistency among pathologists. In addition, it is a time-consuming task. In this work, we have developed an automated diagnosis pipeline to streamline the heart transplant histopathology image quantification and classification, in order to provide objectivity for clinical decision support for pathologists. Traditionally, developing an automated image classification requires a substantial amount of labeled data. However, HTR is a rare condition and the dataset is usually unbalanced. For example, the dataset from DNA Based Transplant Rejection (DTRT) comprises 1,509 rejection tile images and 190 times more non-rejection tile images. To address the small data sample challenge in training the classifiers, we developed a novel strategy that used diffusion model to generate synthetic images of rejection. We conducted comprehensive HTR grade classification comparing results using dataset with synthetic rejection tiles versus the dataset without any synthetic rejection tiles. The introduction of synthetic augmentation resulted in an improvement from 0.781 to 0.981 for sensitivity, and an improvement from 0.984 to over 0.998 in AUROC. This study illustrated that synthetic data augmentation is a feasible strategy in developing AI solutions for rare diseases. In the future, we will expand in this direction to benefit more rare disease clinical decision support development.
Nonlinear Thermal-magneto-electric Equivalent Circuit for L-T Magnetoelectric Laminate

To describe the working process of magnetoelectric (ME) laminate with the equivalent circuit more accurately, the equivalent circuit model is optimized by introducing the temperature field and loss characteristics based on the nonlinear magnetostrictive constitutive relation, the complex modulus and the complex permittivity. Using the nonlinear magnetostrictive constitutive relation, the piezomagnetic coefficient and compliance coefficient of the piezomagnetic layer are calculated. Subsequently, the equivalent circuit is used to calculate the ME field coefficient, and the optimal thickness ratio of the laminate is also discussed. The effects of temperature, prestress and bias magnetic field on piezomagnetic coefficient, compliance coefficient and ME field coefficient are discussed in detail. The optimal bias magnetic field and the peak of ME field coefficient can be adjusted by changing prestress and temperature. Furthermore, the optimal thickness ratio can be obtained to reach the highest ME field coefficient.