Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Analysis and Optimization of Distributed Self-Stabilizing Algorithms

Self-stabilization [14] is a versatile technique for recovery from erroneous behavior due to transient faults or wrong initialization. A system is self-stabilizing if (1) starting from an arbitrary initial state it can automatically reach a set of legitimate states in a finite number of steps and (2) it remains in legitimate states in the absence of faults. Weak-stabilization [25] and probabilisticstabilization [32] were later introduced in the literature to deal with resource consumption of self-stabilizing algorithms and impossibility results. Since the system perturbed by fault may deviate from correct behavior for a finite amount of time, it is paramount to minimize this time as much as possible, especially in the domain of robotics and networking. This type of fault tolerance is called non-masking because the faulty behavior is not completely masked from the user [13]. Designing correct stabilizing algorithms can be tedious. Designing such algorithms that satisfy certain average recovery time constraints (e.g., for performance guarantees) adds further complications to this process. Therefore, developing an automatic technique that takes as input the specification of the desired system, and synthesizes as output a stabilizing algorithm with minimum (or other upper bound) average recovery time is useful and challenging. In this thesis, our main focus is on designing automated techniques to optimize the average recovery time of stabilizing systems using model checking and synthesis techniques. First, we prove that synthesizing weak-stabilizing distributed programs from scratch and repairing stabilizing algorithms with average recovery time constraints are NP-complete in the state-space of the program. To cope with this complexity, we propose a polynomial-time heuristic that compared to existing stabilizing algorithms, provides lower average recovery time for many of our case studies. Second, we study the problem of fine tuning of probabilistic-stabilizing systems to improve their performance. We take advantage of the two properties of self-stabilizing algorithms to model them as absorbing discrete-time Markov chains. This will reduce the computation of average recovery time to finding the weighted sum of elements in the inverse of a matrix. Finally, we study the impact of scheduling policies on recovery time of stabilizing systems. We, in particular, propose a method to augment self-stabilizing programs with k-central and kbounded schedulers to study different factors, such as geographical distance of processes and the achievable level of parallelism.
Dairy Product Consumption and Bladder Cancer Risk: A Meta-Analysis

Abstract To explore the potential relationship between dairy product consumption and bladder cancer risk, we retrieved eligible studies published up to March 15, 2018, via online database search and manual review of the selected articles. Summary relative risk (RR) estimates were calculated using random-effects models based on high to low intake values. Inter-study heterogeneity was explored using stratified analyses of study design, geographic region, or whether studies adjusted for the confounders age, sex, body mass index, smoking, and education level. We extracted data from 16 studies on milk (5,193 subjects) and 10 studies on dairy products (20,434 subjects). The total study population included 220,952 individuals. Dairy product intake and bladder cancer risk were significantly associated, and milk intake and bladder cancer risk more so. Stratified analysis revealed that the trend was more pronounced in case–control studies, and in studies with impact factor <3 and in Asia. The relationship was confirmed after adjusting for sex and Newcastle–Ottawa Scale score of 7 and 8. Our study shows an inverse association between milk consumption and bladder cancer risk.
Gold nano-particles (AuNPs) carrying miR-326 targets PDK1/AKT/c-myc axis in hepatocellular carcinoma

Abstract Abnormal expression of microRNAs (miRNAs) contributes to tumour growth and invasion. MiR-326 expression often down-regulates in several kinds of cancer and low expression of miR-326 is linked with poor prognosis in cancer patients. In the present study, we aimed to explore the modulatory mechanism of miR-326 in hepatocellular carcinoma (HCC). miR-326 expression was significantly decreased in HCC cell lines and tissues. miR-326 decreased HCC cell growth by affecting cell-cycle progression and by promoting apoptosis. In addition, miR-326 inhibited HCC cell invasion by decreasing the EMT phenotype. We found that miR-326 functioned as a tumour suppressor by repressing its down-stream target PDK1. C-myc contributed to miR-326 down-regulation through binding at its promoter and inhibited its expression. Based on these results, we conducted a therapeutic experiment by using gold nano-particles (AuNPs) carrying miR-326. Restoration of miR-326 reduced tumour growth in vivo. Our findings suggest that miR-326 may be a candidate prognostic biomarker and a target for new therapies in HCC patients.
Trends in biomarker discoveries for the early detection and risk stratification of pancreatic cancer using omics studies

Pancreatic cancer, particularly pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal cancers in the world [1]. Five-year survival rates among patients with PDAC remain as low as 9% in the United States [2]. To reduce the mortality of PDAC, screening programs for early diagnosis of PDAC is needed. Screening pancreatic tissuewith invasive or expensivemethods is not feasible for identifying asymptomatic pancreatic cancers in the general populationwithout enrichment of at-risk individuals. Because of the low incidence of PDAC in the general population, PDAC does not currently meet some of the criteria set by the World Health Organization for considering population-based screening as worthwhile [3]. The enrichment and accumulation of high-risk individuals by family history, serologic biomarkers and noninvasive imaging has gained attention as a potentially efficient screening strategy for PDAC. Recently, comprehensive analyses using omics studies (genomics, proteomics and metabolomics) have identified several attractive minimally invasive biomarkers to efficiently detect patients with asymptomatic PDAC from among general populations. Here we discuss trends in biomarker discovery for early detection and risk stratification of asymptomatic pancreatic cancer in clinical settings using omics studies.
The relationship between stress during pregnancy with leptin and cortisol blood concentrations and complications of pregnancy in the mother

Objective: Pregnancy is one of the most stressful periods a woman experiences in her life. The present study was an attempt to determine the relationship between maternal stress during pregnancy and cortisol plus maternal serum leptin concentrations as well as pregnancy outcomes. Material and Methods: This longitudinal study was conducted on 90 pregnant women in Miandoab city between 2015 and 2016. The samples were chosen from mothers with a gestational age of 24 to 28 weeks. The participants were asked to complete Cohen’s Perceived Stress Scale (PSS) and a demographic questionnaire and blood samples were taken from them. The mothers were then tracked with four-week intervals until the time of delivery and were asked to complete Cohen’s PSS each time along with a questionnaire related to maternal outcomes. Again, a blood sample was taken at the time of delivery. Data analysis was performed using SPSS 16. Descriptive statistics, Pearson’s correlation coefficient, and the t-test were employed for analysis. Results: A significant relationship was found between maternal stress and preeclampsia (p=0.008). The relationships between preterm childbirth and maternal cortisol concentrations in weeks 24-28 (p=0.015), and between preterm childbirth and maternal leptin concentrations at the time of delivery (p=0.007) were also found to be significant. Conclusion: Pregnancy and labor, as physically and mentally stressful events, can affect women’s physiologic and psychological indicators. As a consequence, during pregnancy, the cortisol and leptin index changes in response to the activity of the hypothalamic-pituitary axis and autonomic nervous system under stress.
Migraine Progression: A Systematic Review. An Editorial Comment

We are delighted and grateful to receive the AHS Members' Choice Award for our paper, “Migraine Progression: A Systematic Review” and to share this award with Drs. Kranz, Gray and Amrhein for their insightful manuscript, “Spontaneous Intracranial Hypotension: 10 Myths and Misperceptions. ” Clinical experience, case control, and longitudinal studies demonstrate that a subset of individuals with episodic migraine (EM) progress to chronic migraine (CM). Our systematic review compiled the published literature on risk factors for new onset CM and related disorders (transformed migraine and chronic daily headache [CDH]) and rated the strength of evidence for each of the identified risk factors. In this editorial, we consider 3 issues: (1) The nature of the definition of CM; (2) The clinical and public health implications of these findings; and (3) Directions for future research.
The impact of dietary supplementation of arginine during gestation in a commercial swine herd: I. Gilt reproductive performance.

Supplemental Arg during gestation purportedly benefits fetal development. However, the benefits of a gestational Arg dietary strategy in commercial production are unclear. Therefore, objectives of this study examined Arg supplementation during different gestational stages and the effects on gilt reproductive performance. Pubertal gilts (n = 548) were allocated into four treatment groups: Control (n = 143; 0% supplemental Arg) or one of three supplemental Arg (1% as fed) treatments: from 15 to 45 d of gestation (n = 138; Early-Arg); from 15 d of gestation until farrowing (n = 139; Full-Arg); or from 85 d of gestation until farrowing (n = 128; Late-Arg). At farrowing, the number of total born (TB), born alive (BA), stillborn piglets (SB), mummified fetuses (MM), and individual piglet birth weights (BiWt) were recorded. The wean-to-estrus interval (WEI) and subsequent sow reproductive performance (to third parity) was also monitored. No significant effect of supplemental Arg during any part of P0 gestation was observed for TB, BA, SB, or MM (P ≥ 0.29). Offspring BiWt and variation among individual piglet birth weights did not differ (P = 0.42 and 0.89, respectively) among treatment groups. Following weaning, the WEI was similar among treatments (average of 8.0 d ± 0.8 d; P = 0.88). Litter performance over three parities revealed a decrease (P = 0.02) in BA for Early-Arg fed gilts compared to all other treatments, while TB and WEI were similar among treatments over three parities (P > 0.05). There was an increased proportion of sows with average size litters (12 to 16 TB) from the Full-Arg treatment sows (76.8% ± 3.7 %) as compared to Control (58.7% ± 4.2%; P = 0.01), however the proportion of sows with high (> 16 TB) and low (< 12 TB) litters was not different among treatments (P = 0.20). These results suggest that gestational Arg supplementation had a minimal impact on reproductive performance in first parity sows. These data underscore the complexity of AA supplementation and the need for continued research into understanding how and when utilizing a gestational dietary Arg strategy can optimize fetal development and sow performance.
County Variation in Intimate Partner Homicide: A Comparison of Hispanic and Non-Hispanic Victims

Over the past 5 years, intimate partner homicides have increased among Hispanic women, although ethnicity has rarely been brought into macro-level research on intimate partner homicide. These trends have occurred alongside many macro-level changes in the United States. Although both Hispanic and non-Hispanic women are most likely to die at the hands of a partner via a firearm, no study to date has examined the importance of licensed firearm dealer availability in addition to leading macro-level correlates of intimate partner homicide. Using data from the Centers for Disease Control and Prevention’s National Violent Death Reporting System, the current study explores the role of licensed firearm dealer availability, economic disadvantage, and other features of counties to explore ethnic-specific variation in intimate partner homicides from 2010 to 2016. Results from multilevel negative binomial models revealed consistency in the estimated effects of the rate of licensed firearm dealers and divorce on partner homicides across all models, although the significant association of gun stores and intimate partner homicide was witnessed in urban counties for total and non-Hispanic (both Black and White) models only. Important variation also exists across racial and ethnic groups, including well-established correlates of overall intimate partner homicide (i.e., economic disadvantage, rurality, non-intimate homicide rate, and state policies).
Enhanced Camera Calibration for Machine Vision using OpenCV

In several machine vision applications, a fundamental step is to precisely determine the relation between the image of the object and its physical dimension by performing a calibration process. The aim is to devise an enhanced mechanism for camera calibration in order to improve the already existing methods in OpenCV. A good calibration is important when we need to reconstruct a world model or interact with the world as in case of robot, hand-eye coordination. In order to meet the rising demands for higher accuracy various calibration techniques have been developed but they are unable in obtaining precise results. In this paper we propose an enhanced camera calibration procedure using a special grid pattern of concentric circles with special markers. The overall objective is to minimize the re-projection for good camera calibration.
Improved Pedestrian Detection Based on Extended Histogram of Oriented Gradients

In order to further improve pedestrian detection accuracy and avoid the disadvantage of original histogram of oriented gradients (HOG), differential template, overlap ratio and normalization method and so on are improved when HOG features are extracted, then more gradient information are extracted and feature description operators can be obtained which describe human detail features better in lager image regions or detection windows. Considering speed, we select support vector machine (SVM) using linear function kernel as a classifier. Multi-scale detection technique and non maxima suppression method are employed for precisely locating the pedestrians in the image. Experiments show that the human detection system improves detection accuracy and still maintains a relatively satisfactory speed.
Temporal hypermedia for multimedia applications in the World Wide Web

Multimedia applications within the World Wide Web (WWW) have to deal with difficulties like executing within Web pages and being transferred via the Internet. However, the temporal aspects of hypermedia features for continuous media like audio and video resemble all other kinds of multimedia applications. These temporal aspects are discussed in consideration of presentation and authoring facilities. A system architecture and implementation relying on commercial WWW technology is presented.
A high performance frequency and timing synchronization technique for OFDM

In this paper, we propose a new signal-repetition-based frequency and timing synchronization technique for a burst OFDM modem in the severe fading environments typical of broadband wireless communication systems. The repeated synchronization signals are added at the beginning of the radio packets for synchronization agility. The proposed technique employs a weighting function for correlation calculation based on the identical signal repetition approach. The computer simulation results show that the proposed technique significantly improves carrier frequency offset estimation and timing detection performance compared to the conventional scheme without the weighting function.
A hybrid architecture for working memory: Reply to MacDonald and Christiansen (2002).

This article responds to M. C. MacDonald and M. H. Christiansen’s 2002 commentary on the capacity theory of working memory (WM) and its computational implementation, the Capacity-Constrained Collaborative Activation– based Production System (3CAPS). The authors also point out several shortcomings in MacDonald and Christiansen’s proposal for the construal of WM, arguing that at some level of description, their model is a variant of a small subset of the 3CAPS theory. The authors go on to describe how the symbolic and connectionist mechanisms within the hybrid 3CAPS architecture combine to produce a processing style that provides a good match to human sentence comprehension and other types of high-level cognition. The properties of 3CAPS are related to the development of other connectionist, symbolic, and hybrid systems. This article has the goals of (a) refuting some of MacDonald and Christiansen’s (2002) incorrect descriptions of the capacity theory of sentence comprehension as described in Just and Carpenter (1992); (b) pointing out the theoretical and empirical difficulties with MacDonald and Christiansen’s alternative approach and with their simple recurrent network (SRN) model in particular; and (c) pointing out some commonalities between symbolic, connectionist, and hybrid approaches, describing some of their formal properties and their application to a number of cognitive phenomena.
Data Mining for Hazard Elimination through Text Information in Accident Report

Risk management is a management technique to process unexpected damage from various dangers at a minimum cost. It is important for the success of a project. In this paper, we try to extract the information concerning the risk by using the accident data in an actual enterprise. Our purpose is to extract the rule that avoids accidents from the accident data as a rule. Concretely, after making the scenario by using the KeyGraph, we extract the rule by using the rough set.
Active learning in an undergraduate management science course through the use of a mobile computer lab

Our business school's undergraduate degree program includes a required spreadsheet management science course taught at the third-year level. Employers, faculty and students consistently indicated that this course was not successful in teaching management science or even basic spreadsheet modelling skills. To improve students' understanding and retention of the course content, we purchased and implemented a 'mobile computer lab' that could be set up in a regular classroom. We discuss how the lab supported a change to active learning, in which informal student groups would 'discover' management science techniques, and we provide some examples of the exercises we have incorporated in the course. For instructors who are interested in implementing a mobile lab, we also provide details on the infrastructure of the lab, costs, software and hardware security, and classroom logistics.
PRAS: a MAC protocol for wireless ATM networks

The design of an efficient MAC protocol is of paramount importance for the definition of a wireless ATM access. Such a protocol, together with an appropriate traffic scheduler, should guarantee the required QoS for ATM connections. In this paper, we describe the PRAS (polling and reservation access scheme), a TDMA-TDD based MAC protocol with fixed frame duration, using both reservation and polling techniques to assign transmission time slots. In PRAS, each frame consists of variable-length fields, which make the radio access suitable for variable traffic conditions. The scheduling algorithm uses a priority scheme based on the ATM service classes and the maxCTD (cell transfer delay) parameter. A selective-repeat (SR) retransmission procedure is also proposed to correct errored cells due to the noisy channel. Performance results, obtained by simulation, cover different environments and provide many warnings also useful for the in-progress specification activity carried out by the standardization bodies.
Fast IP lookups using a two-trie data structure

IP routing table lookup has been considered as a major bottleneck for high performance routers. We propose a new way to do IP route lookups based on a so-called two trie structure. The two-trie structure shares the nodes representing the front and the rear parts of the prefixes. This results in reducing the number of nodes in the structure. Our results indicate that the memory can be saved around 27% over the standard trie while it still provides the fast lookup (around 1.6 memory accesses in the average case and 8 memory accesses in the worst case). Also, the structure is not based on any assumptions about the distribution of prefix lengths in routing tables. Thus, it can be applied to the larger addresses of IPv6 without affecting the main structure.
A Survey and Comparison of Relational and Non-Relational Database

We report the comparison between the two leading type of Database storage components prevailing in the industry. The Database is largely concerned with managing massive amount of data in a consistent, stable, repeatable and quick manner. The prominent features of both relational as well as non relational databases have been specified which form the basis of the comparison between the two types of database. The relational model is based on mathematical theory(set theory, relational theory) whereas the non-relational databases may or may not have a single groundwork mathematical theory. Relational model is beneficial when it comes to reliability, flexibility, robustness, scalability requirements but in order to cater to the needs of modern applications where the data is huge and generally unstructured; Non-relational databases show true signs of usability here. Based on the characteristics, commonly used tools of relational and non relational databases are mentioned along with brief introduction of the tools. Comparison has been done between the tools to notify the distinctive features of tools of relational and non relational database. Conclusive remarks about the two categories of database have been mentioned.
Energy Efficient Wireless Encryption

The current encryption standard for wireless net- works recommend using the AES cipher in the counter (CTR) mode for confidentiality and in the cipher block chaining (CBC) mode for authentication. In the counter mode, a 128 bit counter is encrypted using the AES into 128 bit keystream which is then XORed with 128 bits of plaintext before transmission. This operation is repeated for the entire frame and results in heavy energy consumption for larger frames. In this paper, we propose a novel cipher called High Diffusion (HD) cipher that securely expands a given 128 bit counter value to a larger 288 bit keystream during encryption, thus reducing the number of encryptions per frame compared to the AES. We show that the HD cipher is as secure as the AES under differential, linear cryptanalysis and the Square attack. Using an experimental set up consisting of a laptop with 1.8 GHz Pentium 4 processor and an Intrinsyc CerfCube with 233 MHz ARM processor we measure the energy consumption of both the AES and the HD cipher encryption operation. We observe that using HD cipher instead of AES for encryption will result in about 40% saving in energy consumption on both the laptop and the CerfCube. We also observe that energy efficiency due to HD cipher is significant for larger frame lengths.