Miracle-dz/UniFAR-FTUs huggingface dataset:
Accelerated Bayesian inference of population size history from recombining sequence data

I present phlash, a new Bayesian method for inferring population history from whole genome sequence data. phlash is population history learning by averaging sampled histories: it works by drawing random, low-dimensional projections of the coalescent intensity function from the posterior distribution of a psmc-like model, and averaging them together to form an accurate and adaptive size history estimator. On simulated data, phlash tends to be faster and have lower error than several competing methods including smc++, msmc2, and FitCoal. Moreover, it provides a full posterior distribution over population size history, leading to automatic uncertainty quantification of the point estimates, as well to new Bayesian testing procedures for detecting population structure and ancient bottlenecks. On the technical side, the key advance is a novel algorithm for computing the score function (gradient of the log-likelihood) of a coalescent hidden Markov model: when there are M hidden states, the algorithm requires. 𝒪(M 2) time and. 𝒪(1) memory per decoded position, the same cost as evaluating the log-likelihood itself using the naïve forward algorithm. This algorithm is combined with a hand-tuned implementation that fully leverages the power of modern GPU hardware, and the entire method has been released as an easy-to-use Python software package.
A general multi-layer area router

This paper presents a general multi-layer area router based on a novel grid construction scheme. The grid construction scheme produces more wiring tracks than the normal uniform grid scheme and accounts for differing design rules of the layers involved. Initial routing performed on the varying capacity grid is followed by a layer assignment stage. Routing completion is ensured by iterating local and global modifications in the layer assignment stage. Our router has been incorporated into the Custom Cell Synthesis project at MCC and has shown improved results for cell synthesis problems when compared with the router Mighty which was used in earlier versions of the project.
A domain-swapped CaMKII conformation facilitates linker-mediated allosteric regulation

Ca2+ signaling plays a key role in physiological processes such as memory formation and cardiac function. Ca2+/calmodulin-dependent protein kinase II (CaMKII) is the primary kinase that responds to Ca2+ inputs in these cells. There are four CaMKII paralogs in mammals which are alternatively spliced in the variable linker region to create upwards of 70 different variants. In this study, we systematically studied different linker regions and determined that the position of charged residues within the linker region modulates the Ca2+/CaM sensitivity of the holoenzyme. We present an X-ray crystal structure of full-length CaMKIIδ that shows a domain-swapped conformation of the subunits within the dodecameric holoenzyme. In this structure, the kinase domain of one subunit is docked onto the hub domain of a different subunit, providing an additional interface within the holoenzyme. Mutations at the equatorial and lateral interfaces revealed that the kinase-hub interaction dissociates as the hub-hub interfaces are disturbed, which led alterations in the stoichiometry of CaMKII holoenzyme and Ca2+/CaM sensitivity. Molecular dynamics simulations of linker-containing domain-swapped and non-domain-swapped CaMKIIs reveal that the domain-swapped configuration facilitates an interaction between the calmodulin binding domain and the variable linker region, such that dynamic electrostatic forces between charges on these segments can modulate the equilibrium between the compact and extended conformational states of the holoenzyme. Small angle X-ray scattering data confirms that a negatively charged linker CaMKII holoenzyme adopts a more compact conformation compared to a positively charged linker. These data support a model where patches of charged linker residues interact with the calmodulin binding domain to allosterically regulate sensitivity to Ca2+/CaM. Our findings provide a new framework for understanding CaMKII structure and allosteric regulation by the variable linker region in Ca2+-sensitive cells.
Lysosomal storage disease proteo/lipidomic profiling using nMOST links ferritinophagy with mitochondrial iron deficiencies in cells lacking NPC2

Lysosomal storage diseases (LSDs) comprised ∼50 monogenic diseases characterized by the accumulation of cellular material in lysosomes and associated defects in lysosomal function, but systematic molecular phenotyping is lacking. Here, we develop a nanoflow-based multi-omic single-shot technology (nMOST) workflow allowing simultaneously quantify HeLa cell proteomes and lipidomes from more than two dozen LSD mutants, revealing diverse molecular phenotypes. Defects in delivery of ferritin and its autophagic receptor NCOA4 to lysosomes (ferritinophagy) were pronounced in NPC2-/- cells, which correlated with increased lyso-phosphatidylcholine species and multi-lamellar membrane structures visualized by cryo-electron-tomography. Ferritinophagy defects correlated with loss of mitochondrial cristae, MICOS-complex components, and electron transport chain complexes rich in iron-sulfur cluster proteins. Strikingly, mitochondrial defects were alleviated when iron was provided through the transferrin system. This resource reveals how defects in lysosomal function can impact mitochondrial homeostasis in trans and highlights nMOST as a discovery tool for illuminating molecular phenotypes across LSDs.
Seekable sockets: a mechanism to reduce copy overheads in TCP-based messaging

This paper extends the traditional socket interface to TCP/IP communication with the ability to seek rather than simply receive data in order. Seeking on a TCP socket allows a user program to receive data without first receiving all previous data on the connection. Through repeated use of seeking, a messaging application or library can treat a TCP socket as a list of messages with the potential to receive and remove data from any arbitrary point rather than simply the head of the socket buffer. Seeking facilitates copy-avoidance between a messaging library and user code by eliminating the need to first copy unwanted data into a library buffer before receiving desired data that appears later in the socket buffer. The seekable sockets interface is implemented in the Linux 2.6. 13 kernel. Experimental results are gathered using a simple microbenchmark that receives data out-of-order from a given socket, yielding up to a 40% reduction in processing time. The code for seekable sockets is now available for patching into existing Linux kernels and for further development into messaging libraries
A2BE: Accountable Attribute-Based Encryption for Abuse Free Access Control

As a recently proposed public key primitive, attribute-based encryption (ABE) (including Ciphertext-policy ABE (CP-ABE) and Key-policy ABE (KP-ABE)) is a highly promising tool for secure fine-grained access control. For the purpose of secure access control, there is, however, still one critical functionality missing in the existing ABE schemes, which is the prevention of key abuse. In particular, two kinds of key abuse problems are considered in this paper, i) illegal key sharing among colluding users and ii) misbehavior of the semi-trusted attribute authority including illegal key (re-)distribution. Both problems are extremely important as in an ABE-based access control system, the attribute private keys directly imply users’ privileges to the protected resources. To the best of our knowledge, such key abuse problems exist in all current ABE schemes as the attribute private keys assigned to the users are never designed to be linked to any user specific information except the commonly shared user attributes. To be concrete, we focus on the prevention of key abuse in CP-ABE in this paper . The notion of accountable CP-ABE (CP-ABE, in short) is first proposed to prevent illegal key sharing among colluding users. The accountability for user is achieved by embedding additional user specific information in the attribute private key issued to the user. To further obtain accountability for the attribute authority as well, the notion of Strong CP-ABE is proposed, allowing each attribute private key to be linked to the corresponding user’s secret that is unknown to the attribute authority. We show how to construct such a Strong CP-ABE scheme and prove its security based on the computational Diffie-Hellman assumption.
PROGRAM ON HOUSING AND URBAN POLICY WORKING PAPER SERIES

We examine the link between increases in housing wealth, ﬁnancial wealth, and consumer spending. We rely upon a panel of 14 countries observed annually for various periods during the past 25 years and a panel of U.S. states observed quarterly during the 1980s and 1990s. We impute the aggregate value of owner-occupied housing, the value of ﬁnancial assets, and measures of aggregate consumption for each of the geographic units over time. We estimate regression models in levels, ﬁrst diﬀerences and in error-correction form, relating consumption to income and wealth measures. We ﬁnd a statistically signiﬁcant and rather large eﬀect of housing wealth upon household consumption.
BMC Medical Informatics and Decision Making

Background: The purpose was to examine how General Practitioners (GPs) use clinical information and rules from guidelines in their decisions on drug treatment for high cholesterol values. Methods: Twenty GPs were presented with six case vignettes and were instructed to think aloud while successively more information about a case was presented, and finally to decide if a drug should be prescribed or not. The statements were coded for the clinical information to which they referred and for favouring or not favouring prescription. Results: The evaluation of clinical information was compatible with decision-making as a search for reasons or arguments. Lifestyle-related information like smoking and overweight seemed to be evaluated from different perspectives. A patient's smoking favoured treatment for some GPs and disfavoured treatment for others. Conclusions: The method promised to be useful for understanding why doctors differ in their decisions on the same patient descriptions and why rules from the guidelines are not followed strictly.
Minimax Differential Dynamic Programming: An Application to Robust Biped Walking

We developed a robust control policy design method in high-dimensional state space by using differential dynamic programming with a minimax criterion. As an example, we applied our method to a simulated five link biped robot. The results show lower joint torques from the optimal control policy compared to a hand-tuned PD servo controller. Results also show that the simulated biped robot can successfully walk with unknown disturbances that cause controllers generated by standard differential dynamic programming and the hand-tuned PD servo to fail. Learning to compensate for modeling error and previously unknown disturbances in conjunction with robust control design is also demonstrated.
Data mining: Prediction for performance improvement of graduate students using classification

Student performance in university courses is of great concern to the higher education where several factors may affect the performance. This paper is an attempt to apply the data mining processes, particularly classification, to help in enhancing the quality of the higher educational system by evaluating student data to study the main attributes that may affect the student performance in courses. For this purpose, we have used data obtained from Vikram University, Ujjain of course B.A. first year student. The classification rule generation process is based on the decision tree as a classification method where the generated rules are studied and evaluated. A system that facilitates the use of the generated rules is built which allows students to predict the final grade in a course under study.
Automating Risk of Bias Assessment for Clinical Trials

Systematic reviews, which summarize the entirety of the evidence pertaining to a specific clinical question, have become critical for evidence-based decision making in healthcare. But such reviews have become increasingly onerous to produce due to the exponentially expanding biomedical literature base. This study proposes a step toward mitigating this problem by automating risk of bias assessment in systematic reviews, in which reviewers determine whether study results may be affected by biases (e.g., poor randomization or blinding). Conducting risk of bias assessment is an important but onerous task. We thus describe a machine learning approach to automate this assessment, using the standard Cochrane Risk of Bias Tool which assesses seven common types of bias. Training such a system would typically require a large labeled corpus, which would be prohibitively expensive to collect here. Instead, we use distant supervision, using data from the Cochrane Database of Systematic Reviews (a large repository of systematic reviews), to pseudoannotate a corpus of 2200 clinical trial reports in PDF format. We then develop a joint model which, using the full text of a clinical trial report as input, predicts the risks of bias while simultaneously extracting the text fragments supporting these assessments. This study represents a step toward automating or semiautomating extraction of data necessary for the synthesis of clinical trials.
Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning

In this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained model’s performance could be attributed to the fact that the generated features are far from the original ones when mapped to the latent space. Therefore, we propose three modifications that mitigate these issues. More specifically, we incorporate the distillation in latent space between the current and previous models to reduce feature drift. Additionally, a latent matching for the reconstruction and original data is proposed to improve generated features alignment. Further, based on the observation that the reconstructions are better for preserving knowledge, we add the cycling of generations through the previously trained model to make them closer to the original data. Our method outperforms other generative replay methods in various scenarios. Code available at https://github.com/valeriya-khan/looking-through-the-past.
An Imitation Learning and Reinforcement Learning Approach to Power System Stabilizer

With the increasing complexity of power system structures, ensuring stability in power systems has become a significant challenge. This paper proposes a combined approach of imitation learning and reinforcement learning for designing power system stabilizers. The method involves collecting input-output data from conventional power system stabilizers as expert demonstrations and utilizing supervised learning to pretrain the policy, thereby initializing the reinforcement learning agent. The agent then interacts with the power system simulation environment to learn the optimal action policy and enhance power system stability. Simulation results on a four-machine two-area power system demonstrate that this technique outperforms traditional power system stabilizers in terms of performance.
Prolactin Receptor and Prolactin Genes Polymorphisms and their Associations with Milk Production Traits in Najdi Sheep

Prolactin (PRL) hormone plays an important role in many biological processes in animals and humans, such as mammogenesis, lactogenesis and galactopoiesis. In dairy cattle, the PRL gene is a potential quantitative trait locus that is used to evaluate milk performance traits. We analyzed the sequence of prolactin ( PRL) and prolactin receptor (PRLR) genes from 30 Saudi native sheep breed in order to investigate whether mutations in this gene can affect milk yield as well as composition. The genetic variability in the prolactin and prolactin receptor (PRLR) genes in Saudi indigenous sheep has been described. Three DNA fragments, a 156 bp fragment from PRL-exon 3 and two fragments represented in intron 1 (215bp) and intron 2 (176bp) of PRLR, were amplified and sequenced from Najdi sheep. The genetic effects of DNA polymorphisms on different traits related to milk production and composition were evaluated. Preliminary analysis showed no significant associations between PRL and PRLR genotypes and milk performance. There was only one haplotype (one version of these segments). Indigenous Najdi breed sheep was monomorphic at exon 3, intron 1 and intron 2. Further work is needed to investigate more individuals of Najdi sheep as well as other Saudi milk producing sheep breeds in order to understand the relationship between variability in PRL and PRLR and the milk yield and composition in these breeds.
TUBULAR‐VESICULAR TRANSFORMATION IN THE CONTRACTILE VACUOLE SYSTEM OF DICTYOSTELIUM

The contractile vacuole complex of Dictyostelium is the paradigm of a membrane system that undergoes tubular‐vesicular transitions during its regular cycle of activities. This system acts as an osmoregulatory organelle in freshwater amoebae and protozoa. It collects fluid in a network of tubules and cisternae, and pumps it out of the cell through transient pores in the plasma membrane. Tubules and vacuoles are interconvertible. The tubular channels are associated with the cortical actin network and are capable of moving and fusing. The contractile vacuole complex is separate from vesicles of the endosomal pathway and preserves its identity in a dispersed state during cell division. We outline techniques to visualize the contractile vacuole system by electron and light microscopy. Emphasis is placed on GFP‐fusion proteins that allow visualization of the dynamics of the contractile vacuole network in living cells. Proteins that control activities of this specialized organelle inDictyostelium have been conserved during evolution and also regulate membrane trafficking in man.
A network distance and graph-partitioning-based clustering method for improving the accuracy of urban hotspot detection

Abstract Clustering is an important approach to identifying hotspots with broad applications, ranging from crime area analysis to transport prediction and urban planning. As an on-demand transport service, taxis play an important role in urban systems, and the pick-up and drop-off locations in taxi GPS trajectory data have been widely used to detect urban hotspots for various purposes. In this work, taxi drop-off events are represented as linear features in the context of the road network space. Based on such representation, instead of the most frequently used Euclidian distance, Jaccard distance is calculated to measure the similarity of road segments for cluster analysis, and further, a network distance and graph-partitioning-based clustering method is proposed for improving the accuracy of urban hotspot detection. A case study is conducted using taxi trajectory data collected from over 6500 taxis during one week, and the results indicate that the proposed method can identify urban hotspots more precisely.
The Oz of Wizard: Simulating the human for interaction research

The Wizard of Oz experiment method has a long tradition of acceptance and use within the field of human-robot interaction. The community has traditionally downplayed the importance of interaction evaluations run with the inverse model: the human simulated to evaluate robot behavior, or “Oz of Wizard”. We argue that such studies play an important role in the field of human-robot interaction. We differentiate between methodologically rigorous human modeling and placeholder simulations using simplified human models. Guidelines are proposed for when Oz of Wizard results should be considered acceptable. This paper also describes a framework for describing the various permutations of Wizard and Oz states.
Development of a novel thermal compression flip chip bonding with pre-applied NCF underfill

In order to overcome problems associated with thermal compression flip chip bonding with post-applied liquid underfill, we have developed a novel process with pre-applied Non Conductive Film (NCF) underfill. This paper describes failure modes in post-applied liquid underfill and the development of the novel NCF process which has several advantages for IC-package assembly. Along with Au bump, this process is applicable to Sn/Ag capped Cu-pillar with ideal electrical connections and high reliability performance.
Identification of 9,17-Dioxo-1,2,3,4,10,19-Hexanorandrostan-5-oic Acid, 4-Hydroxy-2-Oxohexanoic Acid, and 2-Hydroxyhexa-2,4-Dienoic Acid and Related Enzymes Involved in Testosterone Degradation in Comamonas testosteroni TA441

ABSTRACT Comamonas testosteroni TA441 utilizes testosterone via aromatization of the A ring followed by meta-cleavage of the ring. The product of the meta-cleavage reaction, 4,5-9,10-diseco-3-hydroxy-5,9,17-trioxoandrosta-1(10),2-dien-4-oic acid, is degraded by a hydrolase, TesD. We directly isolated and identified two products of TesD as 9,17-dioxo-1,2,3,4,10,19-hexanorandrostan-5-oic acid and (2Z,4Z)-2-hydroxyhexa-2,4-dienoic acid. The latter was a pure 4Z isomer. 2-Hydroxyhexa-2,4-dienoic acid was converted by a hydratase, TesE, and the product isolated from the reaction solution was identified as 2-hydroxy-4-hex-2-enolactone, indicating the direct product of TesE to be 4-hydroxy-2-oxohexanoic acid.
Changes in Protein Profile Induced by Glyphosate, Diclofop-Methyl and Pendimethalin in Herbicide-tolerant Fungi

In the present investigation an attempt has been made to study glyphosate, Diclofop-methyl and Pendimethalin and fenvalerate induced changs in protein submits the herbicide-tolerant fungi isolated from pesticides polluted-soil. Severely loss in the total soluble cell ions (SCI) and total cell protein percentage (TCPC) concentrations was observed. For glyphosate, Aspergillus flavus (86.30%) was the most affected one, followed by Penicillium spiculisporus (76.30%) , Penicillium verruculosum (64.40%) and Alternaria tenuissima (64%), respectively. The other fungal strains exhibited <50% in total SCI. For Pendimethalin, Alternaria tenuissima (54.01%) was the most affected fungi followed by Penicillium spinulosum (50.68%), respectively. The other fungal strains exhibited <50% in total SCI. For Diclofop-methyl, Penicillium spiculisporus (74.20%) was the most affected fungi followed by Aspergillus tamarii (70.67%), Aspergillus niger (56.16%), Aspergillus terreus (54.67%) and Alternaria tenuissima (58.82%) , respectively. The other fungal strains exhibited d” 50% SCI. The loss of TCPC by Glyphosate, Alternaria tenuissima (64.71%) was the most effected fungi, followed by Penicillium spiculisporus (57.14%) , respectively. The other fungal strains exhibited <50%. For Pendimethalin, A. terreus (54.29%) was the most affected fungi followed by Alternaria tenuissima (50.00%), respectively. The other fungal strains exhibited <50%. For Diclofop-methyl, Penicillium spiculisporus (60%) , followed by Alternaria tenuissima (58.82%) , Aspergillus tamarii (55.56%), respectively. The other fungal strains exhibited <50%. The results proved changes in protein profile induced in herbicide-tolerant fungi.