Miracle-dz/UniFAR-FTUs huggingface dataset:
An Implicit Representation and Iterative Solution of Randomly Sketched Linear Systems

Randomized linear system solvers have become popular as they have the potential to reduce floating point complexity while still achieving desirable convergence rates. One particularly promising class of methods, random sketching solvers, has achieved the best known computational complexity bounds in theory, but is blunted by two practical considerations: there is no clear way of choosing the size of the sketching matrix apriori; and there is a nontrivial storage cost of the projected system. In this work, we make progress towards addressing these issues by implicitly generating the sketched system and solving it simultaneously through an iterative procedure. As a result, we replace the question of the size of the sketching matrix with determining appropriate stopping criteria; we also avoid the costs of explicitly representing the sketched linear system; and our implicit representation also solves the system at the same time, which controls the per-iteration computational costs. Additionally, our approach allows us to generate a connection between random sketching methods and randomized iterative solvers (e.g., randomized Kaczmarz method). As a consequence, we exploit this connection to (1) produce a stronger, more precise convergence theory for such randomized iterative solvers under arbitrary sampling schemes (i.i.d., adaptive, permutation, dependent, etc.), and (2) improve the rates of convergence of randomized iterative solvers at the expense of a user-determined increases in per-iteration computational and storage costs. We demonstrate these concepts on numerical examples on forty-nine distinct linear systems.
Chirality in non-Hermitian photonics

Chirality is ubiquitous from microscopic to macroscopic phenomena in physics and biology, such as fermionic interactions and DNA duplication. In photonics, chirality has traditionally represented differentiated optical responses for right and left circular polarizations. This definition of optical chirality in the polarization domain includes handedness-dependent phase velocities or optical absorption inside chiral media, which enable polarimetry for measuring the material concentration and circular dichroism spectroscopy for sensing biological or chemical enantiomers. Recently, the emerging field of non-Hermitian photonics, which explores exotic phenomena in gain or loss media, has provided a new viewpoint on chirality in photonics that is not restricted to the traditional polarization domain but is extended to other physical quantities such as the orbital angular momentum, propagation direction, and system parameter space. Here, we introduce recent milestones in chiral light-matter interactions in non-Hermitian photonics and show an enhanced degree of design freedom in photonic devices for spin and orbital angular momenta, directionality, and asymmetric modal conversion.
AlphaClean: Automatic Generation of Data Cleaning Pipelines

The analyst effort in data cleaning is gradually shifting away from the design of hand-written scripts to building and tuning complex pipelines of automated data cleaning libraries. Hyper-parameter tuning for data cleaning is very different than hyper-parameter tuning for machine learning since the pipeline components and objective functions have structure that tuning algorithms can exploit. This paper proposes a framework, called AlphaClean, that rethinks parameter tuning for data cleaning pipelines. AlphaClean provides users with a rich library to define data quality measures with weighted sums of SQL aggregate queries. AlphaClean applies generate-then-search framework where each pipelined cleaning operator contributes candidate transformations to a shared pool. Asynchronously, in separate threads, a search algorithm sequences them into cleaning pipelines that maximize the user-defined quality measures. This architecture allows AlphaClean to apply a number of optimizations including incremental evaluation of the quality measures and learning dynamic pruning rules to reduce the search space. Our experiments on real and synthetic benchmarks suggest that AlphaClean finds solutions of up-to 9x higher quality than naively applying state-of-the-art parameter tuning methods, is significantly more robust to straggling data cleaning methods and redundancy in the data cleaning library, and can incorporate state-of-the-art cleaning systems such as HoloClean as cleaning operators.
An Effective Dichotomy for the Counting Constraint Satisfaction Problem

Bulatov [Proceedings of the $35$th International Colloquium on Automata, Languages and Programming (Part 1), Lecture Notes in Comput. Sci. 5125, Springer, New York, 2008, pp. 646--661] gave a dichotomy for the counting constraint satisfaction problem \#CSP. A problem from \#CSP is characterized by a constraint language $\Gamma\! $, a fixed, finite set of relations over a finite domain $D$. An instance of the problem uses these relations to constrain an arbitrarily large finite set of variables. Bulatov showed that the problem of counting the satisfying assignments of instances of any problem from \#CSP is either in polynomial time (FP) or is \#P-complete. His proof draws heavily on techniques from universal algebra and cannot be understood without a secure grasp of that field. We give an elementary proof of Bulatov's dichotomy, based on succinct representations, which we call frames, of a class of highly structured relations, which we call strongly rectangular. We show that these are precisely the relation.
Duplicate Removal for Overlapping Clusters: A Study Using Social Media Data

The social media is a labyrinth of information which when uncovers, provides a deep insight into the real-world happenings. In this study, we use social media Twitter to create user groups or clusters using the retweet and reply directed links. The main idea behind creating the groups is to figure out a user’s best suited place and to generate crisp clusters. Each user forms a group and thus numerous overlapping groups or clusters are created. To get crisp clusters, we present an algorithm for removing duplicates in cluster configurations that feature a significant amount of overlapping. The idea presented in this paper is that we consider numerous overlapping clusters in a cluster set and proceed in a manner where each cluster is compared with a set of users. The user set is created from these clusters. The proposed algorithm deletes all duplicates and is compared to a naive algorithm. Moreover, a modified algorithm is also proposed whereby selected duplicates are kept based on most significant position of the user among all clusters in the configuration. This does not guarantee that all duplicates will be removed. But, as shown in the study a majority of duplicates are removed. Both the proposed and modified algorithm are lot faster than the naive one. This domain was selected because its a domain where we wish to identify unique user communities (clusters) and where large amount of overlap typically exists. After duplicate elimination, we are left with few clusters which are much bigger in size than other clusters in the cluster set.
Modeling and simulation experiments of trail network formation by non-diffusion-based mobile molecular communication networks

In non-diffusion-based mobile molecular communication networks, bio-nanomachines use non-diffusive surface-bound molecules to form trail networks in order to coordinate their behavior. In this paper, we consider three types of bio-nanomachine responsible for trail network formation: non-reactive, attractive and repulsive. All the three types of bio-nanomachine deposit trail-forming molecules in the environment, while the non-reactive type walks randomly, the attractive type moves preferentially to the higher concentration of the molecules, and the repulsive type moves preferentially to the lower concentration of the molecules. We first model the mobility of the three types of bio-nanomachine using a Langevin equation. We then show through simulation experiments that the three types of bio-nanomachine form characteristic trail networks, which can be used depending on goals of mobile molecular communication networks.
Box-Driven Class-Wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation

Semantic segmentation has achieved huge progress via adopting deep Fully Convolutional Networks (FCN). However, the performance of FCN based models severely rely on the amounts of pixel-level annotations which are expensive and time-consuming. To address this problem, it is a good choice to learn to segment with weak supervision from bounding boxes. How to make full use of the class-level and region-level supervisions from bounding boxes is the critical challenge for the weakly supervised learning task. In this paper, we first introduce a box-driven class-wise masking model (BCM) to remove irrelevant regions of each class. Moreover, based on the pixel-level segment proposal generated from the bounding box supervision, we could calculate the mean filling rates of each class to serve as an important prior cue, then we propose a filling rate guided adaptive loss (FR-Loss) to help the model ignore the wrongly labeled pixels in proposals. Unlike previous methods directly training models with the fixed individual segment proposals, our method can adjust the model learning with global statistical information. Thus it can help reduce the negative impacts from wrongly labeled proposals. We evaluate the proposed method on the challenging PASCAL VOC 2012 benchmark and compare with other methods. Extensive experimental results show that the proposed method is effective and achieves the state-of-the-art results.
LinkMirage: How to Anonymize Links in Dynamic Social Systems

Social network based trust relationships present a critical foundation for designing trustworthy systems, such as Sybil defenses, secure routing, and anonymous/censorshipresilient communications. A key issue in the design of such systems, is the revelation of users' trusted social contacts to an adversary-information that is considered sensitive in today's society. In this work, we focus on the challenge of preserving the privacy of users' social contacts, while still enabling the design of social trust based applications. First, we propose LinkMirage, a community detection based algorithm for anonymizing links in social network topologies; LinkMirage preserves community structures in the social topology while anonymizing links within the communities. LinkMirage considers the evolution of the social network topologies, and minimizes privacy leakage due to temporal dynamics of the system. Second, we define metrics for quantifying the privacy and utility of a time series of social topologies with anonymized links. We analyze the privacy and utility provided by LinkMirage both theoretically, as well as using real world social network topologies: a Facebook dataset with 870K links and a large-scale Google+ dataset with 940M links. We find that our approach significantly outperforms the existing state-of-art. Finally, we demonstrate the applicability of LinkMirage in real-world applications such as Sybil defenses, reputation systems, anonymity systems and vertex anonymity. We also prototype LinkMirage as a Facebook application such that real world systems can bootstrap privacy-preserving trust relationships without the cooperation of the OSN operators.
Cloning, sequence analysis and phylogeny of connexin43 isolated from American black bear heart

Conduction in the heart requires gap junctions. In mammalian ventricular myocytes these consist of connexin43 (Cx43). Hearts of non-hibernating species display conduction disturbances at reduced temperatures. These may exacerbate into lethal arrhythmias. Hibernating species are protected against these arrhythmias by a non-resolved mechanism. To analyze whether the amino acid composition of Cx43 from the hibernating American black bear displays specific features, we cloned the full coding sequence of Ursus americanus Cx43 and compared with that of other (non)hibernating species. UaCx43 displays 99.7% identity to rabbit Cx43 at the amino acid level. No specific features were observed in UaCx43 when compared to previously cloned Cx43 from hibernating and non-hibernating mammals. Phylogenetic tree reconstruction of this and other published full-length Cx43 sequences reveals a very high level of conservation from fish to men. Finally, one of the previously identified six mammalian characteristic amino acids, is not conserved in the black bear.
Factors Associated With Outcome in Heart Failure With Preserved Ejection Fraction: Findings From the Irbesartan in Heart Failure With Preserved Ejection Fraction Study (I-PRESERVE)

Background—The determinants of prognosis in patients with heart failure and preserved ejection fraction (HF-PEF) are poorly documented. Methods and Results—We evaluated data from 4128 patients in the I-PRESERVE trial (Irbesartan in Heart Failure with Preserved Ejection Fraction Study). Multivariable Cox regression models were developed using 58 baseline demographic, clinical, and biological variables to model the primary outcome of all-cause mortality or cardiovascular hospitalization (1505 events), all-cause mortality (881 events), and HF death or hospitalization (716 events). Log N-terminal pro–B-type natriuretic peptide, age, diabetes mellitus, and previous hospitalization for HF were the most powerful factors associated with the primary outcome and with the HF composite. For all-cause mortality, log N-terminal pro–B-type natriuretic peptide, age, diabetes mellitus, and left ventricular EF were the strongest independent factors. Other independent factors associated with poor outcome included quality of life, a history of chronic obstructive lung disease, log neutrophil count, heart rate, and estimated glomerular filtration rate. The models accurately stratified the actual 3-year rate of outcomes from 8.1% to 59.9% (primary outcome) 2.7% to 36.5% (all-cause mortality), and 2.1% to 38.9% (HF composite) for the lowest to highest septiles of predicted risks. Conclusions—In a large sample of elderly patients with HF and preserved EF enrolled in I-Preserve, simple clinical, demographic, and biological variables were associated with outcome and identified subgroups at very high and very low risk of events. Clinical Trial Registration—URL: http://www.clinicaltrials. gov. Unique identifier: NCT00095238.
Hamstring flexibility in young women following passive stretch and muscle energy technique.

BACKGROUND Research is limited and controversial on the effectiveness of various stretching methods on muscle lengthening. OBJECTIVE Studying the effectiveness of static stretch and muscle energy technique on the flexibility of hamstring muscles. METHODS Thirty young females (20-25 yrs old) participated voluntarily in this study. Subjects were randomly assigned to two groups: static stretch group (controls; n=15) and muscle energy technique (MET) group (experimental; n=15). The control group underwent ten sessions of static stretches of hamstring muscle, and the experimental group was assigned to ten sessions of MET at 50% voluntary isometric contraction. Hamstring flexibility was evaluated by passive knee extension test at baseline and again following interventions. RESULTS Both treatment methods were capable of significantly improving the shortness of hamstring muscles (P< 0.01); and no considerable difference was observed between the methods. CONCLUSION Ten sessions of hamstring stretches in normal young women using either static stretch or MET had similar effect on restoring flexibility to hamstrings.
A Multi-Paradigm Approach to Teaching Students Embedded Systems Design using FPGAs and CPLDs

To create optimal embedded electronic systems, it is essential to ensure all implementation options are considered, and students of electronics and computer engineering must be educated in hardware, software and firmware. We begin by reviewing in an educational context various implementation techniques. These include commercial microcontrollers, custom instruction set architectures (ISA), Field Programmable Gate Arrays (FPGAs) for `soft-core' processors and dedicated digital `engines', as well as Complex Programmable Logic Devices (CPLDs) for interface management. Thereafter, we describe our work to create a platform that incorporates the above but is extended to include software development and tools. Regarding ISAs, we use an FPGA configured with a soft-core ARM Cortex-M1 32-bit processor but also introduce a custom hybrid RISC/CISC 12-bit processor called VIP. This helps students explore and compare multiple soft-core implementation issues. Furthermore, unlike most proprietary platforms, we can provide students with the HDL code of all our peripherals and interfaces. Especially those for the address and data lines used communicate with devices on our associated custom Teaching Auxiliary Board (TAB); which itself uses a CPLD programmed to provide features such as bus handshake, protocol conversions, timers, interrupts and simulation of `slow memory locations'. We believe that our holistic approach provides exceptional learning opportunities to show how implementations may be partitioned across FPGAs and CPLDs acting as dedicated programmed logic or programmable soft-core processors.
Attack of the 50 Foot Botnet

The trend toward smaller botnets may be more dangerous in terms of large-scale attacks like distributed denials of service. We examine the possibility of “super-botnets,” networks of independent botnets that can be coordinated for attacks of unprecedented scale. For an adversary, super-botnets would also be extremely versatile and resistant to countermeasures. Our simulation results shed light on the feasibility and structure of super-botnets and some properties of their command-and-control mechanism. Possible defenses against the threat of super-botnets are suggested.
A new genetic selection identifies essential residues in SecG, a component of the Escherichia coli protein export machinery.

The signal sequence of the murine serine protease inhibitor PAI‐2 promotes alkaline phosphatase export to the E. coli periplasm. However, high level expression of this chimeric protein interferes with cell growth. Since most suppressors of this toxic phenotype map to secA and secY, growth arrest results from a defective interaction of the chimeric protein with the export machinery. We have characterized suppressors which map in secG, a newly defined gene of the export machinery. All single amino acid substitutions map to three adjacent codons. These secG mutants have a weak Sec phenotype, as determined by their effect on export mediated by wild‐type and mutant signal sequences. Whilst a secG disruption allele also confers a weak Sec phenotype, it does not suppress the toxicity of the chimeric protein. This difference results from a selective effect of the secG suppressors on the kinetics of export mediated by the PAI‐2 signal sequence. Using a malE signal sequence mutant, which has a Mal‐phenotype in secG mutant strains, we have isolated extragenic Mal+ suppressors. Most suppressors map to secY, and several are allele‐specific. Finally, SecG overexpression accelerates the kinetics of protein export, suggesting that there are two types of functional translocation complexes: with or without SecG.
Inactivation of arf-bp1 Induces p53 Activation and Diabetic Phenotypes in Mice*

Background: ARF-BP1 is involved in Mdm2-independent p53 degradation. Results: Inactivation of arf-bp1 in mice resulted in p53 activation and embryonic lethality. Inactivation of arf-bp1 in pancreatic β-cells resulted in diabetes, which was partially rescued by loss of p53. Conclusion: p53 is critically regulated by ARF-BP1 in vivo and in β-cells. Significance: ARF-BP1 is important for maintaining pancreatic β-cell homeostasis in aging mice. It is well accepted that the Mdm2 ubiquitin ligase acts as a major factor in controlling p53 stability and activity in vivo. Although several E3 ligases have been reported to be involved in Mdm2-independent p53 degradation, the roles of these ligases in p53 regulation in vivo remain largely unknown. To elucidate the physiological role of the ubiquitin ligase ARF-BP1, we generated arf-bp1 mutant mice. We found that inactivation of arf-bp1 during embryonic development in mice resulted in p53 activation and embryonic lethality, but the mice with arf-bp1 deletion specifically in the pancreatic β-cells (arf-bp1FL/Y/RIP-cre) were viable and displayed no obvious abnormality after birth. Interestingly, these mice showed dramatic loss of β-cells as mice aged, and >50% of these mice died of severe diabetic symptoms before reaching 1 year of age. Notably, the diabetic phenotype of these mice was largely reversed by concomitant deletion of p53, and the life span of the mice was significantly extended (p53LFL/FL/arf-bp1FL/Y/RIP-cre). These findings underscore an important role of ARF-BP1 in maintaining β-cell homeostasis in aging mice and reveal that the stability of p53 is critically regulated by ARF-BP1 in vivo.
Visual analysis framework for two-person interaction

In this paper, a novel approach to two person interaction method is presented in which pose representation is based on the feature of silhouette images. Today human activity recognition and analysis has a tremendous potential to impact a wide range of applications from surveillance to human computer interfaces to content based video retrieval. Specifically, the proposed method makes use of human silhouettes to classify actions and interactions of human present in a scene video. The classes of interactions will include punching, pushing, kicking, hand-shaking, and hugging. Moreover, the detected interactions are further divided into violence or non-violence so that a suitable security measures would be taken. To confirm the validity of the proposed method, the experimental results are carried out by using the publicly available dataset.
Evaluation of Ki-67 antigen expression in the vaginal epithelium of castrated female rats treated with raloxifene and tamoxifen: a comparative study

Abstract Objective: The aim of this study was to evaluate the effects of raloxifene and tamoxifen on Ki-67 antigen expression in the vaginal epithelium of castrated rats. Material and methods: Thirty-nine virgin, adult, castrated female Wistar–Hannover rats were randomly divided into three groups: Group I (control, n = 13), Group II (raloxifene, n = 13) and Group III (tamoxifen, n = 13). After confirmation of their hypoestrogenic state, the rats were given 0.5 ml of propylene glycol (vehicle), 750 μg of raloxifene or 250 μg of tamoxifen, respectively, by gavage, for 30 days. On the 31st day, the rats were euthanized and their vaginas removed and fixed in 10% buffered formalin for of Ki-67 immunohistochemical evaluation. Data were analyzed using Levene’s test and Tukey’s method (p < 0.05). Results: Mean Ki-67 expression in groups I, II and III was 27 ± 2.6, 32.3 ± 1.9 and 43.7 ± 3.5, respectively. In Group III (tamoxifen), there was a greater proportion of stained cells compared to Groups I and II (p < 0.0003), with no statistically significant difference between Groups I and II (p = 0.3626). Conclusions: The present results show that tamoxifen significantly increased cell proliferation in the vaginal epithelium of the castrated rats and no difference between the raloxifene and control groups.