Miracle-dz/UniFAR-FTUs huggingface dataset:
Shifting Patterns in Wisconsin Crime Rates

In this study we explore shifting patterns in crime across Wisconsin counties between 1990 and 2000. Building on the three core ecological theories of criminology including strain/anomie, social disorganization and economic rational choice theories we hypothesis that socioeconomic well-being can be used to identify predictable patterns of change in crime. The data generally support the notion that higher levels of socioeconomic well-being at the beginning of the period are associated with lower levels of both violent and property crime at the end of the study period.
Discriminative resolution enhancement in acoustic modelling

The accuracy of the acoustic models in large vocabulary recognition systems can be improved by increasing the resolution in the acoustic feature space. This can be obtained by increasing the number of Gaussian densities in the models by splitting of the Gaussians. This paper proposes a novel algorithm for this splitting operation. It is based on the phonetic decision tree used for the state tying in context dependent modelling. The advantage of the method is that it improves the capability of the acoustic models to discriminate between the different tied states. The proposed splitting algorithm was evaluated on the Wall Street Journal recognition task. Comparison with a commonly used splitting algorithm clearly shows that our method can provide smaller (thus faster) acoustic models and results in lower error rates.
On the frequency of N${_2}$H$^+$ and N${_2}$D${^+}$

Context. Dynamical studies of prestellar cores search for small velocity differences between different tracers. The highest radiation frequency precision is therefore required for each of these species. Aims. We want to adjust the frequency of the first three rotational transitions of N 2 H + and N 2 D + and extrapolate to the next three transitions. Methods. We compare N 2 H + and N 2 D + to NH 3 , the frequency of which is more accurately known and which has the advantage of being spatially coexistent with N 2 H + and N 2 D + in dark cloud cores. With lines among the narrowest, and the N 2 H + and NH 3 emitting region among the largest, L183 is a good candidate for comparing these species. Results. A correction of ~10 kHz for the N 2 H + ( J : 1-0) transition is found (~0.03 km s -1 ). Similar corrections from a few m s -1 up to ~0.05 km s -1 compared to previous astronomical determinations are reported for the other transitions (N 2 H + ( J : 3-2) and N 2 D + ( J : 1-0), ( J : 2-1), and ( J : 3-2)). Einstein spontaneous-decay coefficients ( A ul ) are included.
Detection of Protein Subcellular Localization Based on Syntactic Dependency Paths

Despite the widespread use of computers in biological research, the end result of almost all scientific experiments is a publication in the form of texts. So, many studies have sought to extract information from biomolecular text using natural language processing technology. Previous studies have asserted that linguistic information is useful for information extraction from text. In particular, syntactic relations among linguistic information are good for detection of protein interactions, protein subcellular localization, and so on. However, previous systems in detecting protein subcellular localization use only shallow syntactic parsers, and they did not show good performance. To improve performance in detecting protein subcellular localization, this paper proposes a three-step method based on a full syntactic dependency parser. In the first step, we construct syntactic dependency paths from each protein to its location candidate. In the second step, we retrieve root information of the syntactic paths. In the last step, we extract syntactic patterns of protein sub-trees and those of location sub-trees. According to the root information and syntactic patterns of sub-trees, we extract correct (protein, localization) pairs. Even without biomolecular knowledge, our method shows reasonable performance. In the experimental results using Medline abstracts data, our proposed method gave an F-measure of 76% for training data and 60% for test data, significantly outperforming previous methods. We also describe the contributions of root information and syntactic patterns of sub-trees to the performance.
Self-Adaptive Containers: Functionality Extensions and Further Case Study

—As the number of execution environments and application contexts rises exponentially, ever-changing non-functional requirements can lead to repeated code refactoring. In addition, scaling up software to support large input sizes may require major modiﬁcation of code. To address these challenges, we have previously proposed a framework of self-adaptive containers which can automatically adjust their resource usage to meet Service Level Objectives and dynamically deploy the techniques of out-of-core storage and probabilistic data structures. A prototype with limited functionalities was implemented and applied to explicit state space exploration to prove the viability of our framework. In this paper, we broaden the library’s functionalities through support for the important container class of key-value stores and integration of priority queues’ functionalities into our previously-developed container class. We then utilise them in a new case study centred on route planning, adopting Dijkstra’s shortest path algorithm. For this, a graph representing the full USA road network, which contains approximately 24 million nodes and 58 million arcs, is input to the algorithm so as to ﬁnd the shortest paths from a random node to all the other nodes. The experimental results have shown that, under particular Service Level Objectives our library reduces update time by 21.4%, primary memory usage of node storage by 85.3%, and primary memory consumption required by the priority queue by 78%, compared with the Standard Template Library.
THE ACCOUNTING ETHICS COURSE RECONSIDERED

The debate on the effect of teaching ethics to accounting students has continued for decades. Prior studies on the effects of covering specific types of content on student ethics, including ethics theory and professional codes with accounting-specific cases and examples, have produced mixed results. This study examines the impact of a semester long accounting ethics course which incorporates a formal ‘Ethics Education Framework and associated Toolkit’ on students’ ethical development The authors would like to acknowledge the students from UWEC who participated in the study, Dennis Bline (editor), and the reviewers, for their helpful comments that greatly improved this paper.
Performance Analysis Survey of Various SAR Image Despeckling Techniques

Over the past four decades, the Synthetic Aperture Radar (SAR) imagery has become a beneficial and important application over the optical satellite imagery because of its ability to operate in any weather conditions. However, these images are affected with granular noise termed as Speckle noise. This noise affects the overall quality of the image adversely and hence hinders the observation of vital and crucial information present in the image. Thus, it has become essential to remove this speckle noise using suitable techniques. This paper presents the various important techniques available till date for the removal of speckle noise from SAR images and each technique with its own advantages and limitations are described. It also presents qualitative and quantitative measures of various techniques.
Immunohistochemical analysis of estrogen receptors in prostate and clinical correlation in men with benign prostatic hyperplasia

Purpose Estrogens act through interaction with 2 receptor subtypes, ER alpha (ERα) and ER beta (ERβ), in human prostate. The aim of the present study was to semiquantitatively assess the differential expression of ER subtypes in human benign prostatic hyperplasia (BPH) by use of immunocytochemistry (IHC) methods and to explore their relationship with various measures of BPH. Materials and Methods A total of 45 patients with BPH undergoing transurethral resection of the prostate and 22 patients with bladder cancer with normal prostate undergoing surveillance cystoscopy were studied as cases and controls, respectively. Quantitative immunolabeling of ER subtypes was scored by use of a semiquantitative scale. Also, correlations were assessed between ER levels in prostate and various measures of BPH. Results Overall, we found strong immunostaining for ERα in stroma and for ERβ in epithelium, respectively. The IHC score for ERα differed significantly between BPH patients and controls in both stroma (p≤0.001) and epithelium (p=0.008), respectively. The ERβ IHC score was also significantly higher in the epithelium of BPH patients (p=0.01). Also, we found a significant correlation between prostatic ER levels and various clinical measures of BPH. Conclusions ERs may play an important role in the pathogenesis of BPH.
Dice the TX power — Improving Awareness Quality in VANETs by random transmit power selection

Future safety-related vehicular applications require reliable information exchange provided by cooperative Vehicular Ad-hoc NETworks (VANETs). Although the vehicular WLAN standard IEEE 802.11p has been adapted to the challenging vehicular environment, it has not been adapted to the stringent communication requirements imposed by vehicular applications. In particular, broadcast transmissions are mostly periodic and initiated at common TX powers. This makes potential interferences recurring instead of spurious and lowers the performance of medium access for vehicular applications. In this paper, we propose to leverage recurring interferences by randomly selecting each TX power following a given probability distribution. Such randomization reduces the chances of recurring interferences, and the probability distribution provides control to the applications regarding the required Awareness Quality, in particular by providing a higher Awareness Quality at close range. This concept also reduces congestions by transmitting less at high distances. It is transparent to the applications, and manages to improve the Awareness Quality in a dense highway by a factor 2 to 20, yet at a factor 2 to 3 lower channel load.
Effects of right ventricular septal versus apical pacing on plasma natriuretic peptide levels

Background: To investigate the contribution of right ventricular (RV) pacing sites to the cardiac function, this study compares plasma B-type natriuretic peptide (BNP) levels during RV septal and apical pacing in patients implanted with a pacemaker. Materials and Methods and Results: Seventy-four consecutive patients with indication for permanent pacing were included. To provide for the possibility of appropriate subgroup analyses, patients were stratified according to their pacing mode into two groups: Those with dual chamber DDD(R)/VDD pacemakers (41 patients, mean age 54.1±18.4 years), and those with single chamber VVI pacemakers (33 patients, mean age 60.6±18.4 years). A prospective single-blinded randomized design was used. Randomization (1:1 way) was between lead placement on the RV septum or RV apex and occurred during the implant in both groups. Compared to baseline, a significant decrease in BNP (429.8±103 pg/ml and 291.7±138 pg/ml, respectively) levels was observed during DDD(R) /VDD pacing after two months. In contrast, during VVI (R) pacing, a significant increase in BNP levels was observed (657.5±104 pg/ml and 889.5±139 pg/ml, respectively). To determine the impact of pacing sites on cardiac function, we assessed the changes in BNP levels in each group separately. Despite the significant difference in the pattern of changes between the two groups (P < 0.02), no significant changes were observed within groups regarding the acute effect of the pacing site (RV apex vs. RV septal) on BNP levels (P=NS). Conclusions: Our main result showed no significant differences between pacing sites and concluded that hemodynamic improvement could be substantially influenced by pacing mode, more than by pacing site.
DRAFT 3 / 4 / 07 Bayesian Generic Priors for Causal Learning

We present a Bayesian model of causal learning that incorporates generic priors on distributions of weights representing potential powers to either produce or prevent an effect. These generic priors favor necessary and sufficient causes. The NS power model couples these priors with a causal generating function derived from the power PC theory (Cheng, 1997). We test this and other alternative Bayesian models using the strategy of computational cognitive psychophysics, fitting multiple data sets in which several parameters are varied parametrically across multiple types of judgments. The NS power model accounts for a wide range of data concerning judgments of both causal strength (the power of a cause to produce or prevent an effect) and causal structure (whether or not a causal link exists). For both types of causal judgments, a generic prior favoring a cause that is jointly necessary and sufficient explains interactions involving causal direction (generative versus preventive causes). For structure judgments, an additional prior that a new candidate cause will be deterministic (i.e., sufficient or else ineffective) explains why people’s causal structure judgments are based primarily on causal power and the base rate of the effect, rather than sample size. Alternative Bayesian formulations that lack either causal power assumptions or generic priors for necessity and sufficiency proved inadequate. Broader implications of the Bayesian framework for human learning are discussed.
From Words to Corpora: Recognizing Translation

This paper presents a technique for discovering translationally equivalent texts. It is comprised of the application of a matching algorithm at two different levels of analysis and a well-founded similarity score. This approach can be applied to any multilingual corpus using any kind of translation lexicon; it is therefore adaptable to varying levels of multilingual resource availability. Experimental results are shown on two tasks: a search for matching thirty-word segments in a corpus where some segments are mutual translations, and classification of candidate pairs of web pages that may or may not be translations of each other. The latter results compare competitively with previous, document-structure-based approaches to the same problem.
PAPER Special Section on Quality of Communication Services Improving Quality of Life Benefit of Network Coding for Probabilistic Packet Marking and Collecting Coupons from Different Perspectives at the Collector

SUMMARY Probabilistic Packet Marking (PPM) is a scheme for IP traceback where each packet is marked randomly with an IP address of one router on the attack path in order for the victim to trace the source of attacks. In previous work, a network coding approach to PPM (PPM+NC) where each packet is marked with a random linear combination of router IP addresses was introduced to reduce number of packets required to infer the attack path. However, the previous work lacks a formal proof for benefit of network coding to PPM and its proposed scheme is restricted. In this paper, we propose a novel method to prove a strong theorem for benefit of network coding to PPM in the general case, which compares different perspectives (interests of collecting) at the collector in PPM+NC scheme. Then we propose Core PPM+NC schemes based on our core network coding approach to PPM. From experiments, we show that our Core PPM+NC schemes actually require less number of packets than previous schemes to infer the attack path. In addition, based on the relationship between Coupon Collector’s Problem (CCP) and PPM, we prove that there exists numerous
HIGH-DIMENSIONAL HIERARCHICAL OLAP : A PREFIX- INDEX HIERARCHICAL CUBING APPROACH

The pre-computation of data cubes is critical for improving the response time of OLAP(online analytical processing) systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional OLAP, it might not be practical to build all these cuboids and their indices. In this paper, we propose a multi-dimensional hierarchical cubing algorithm, Prefix-index hierarchical cubing, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low dimensional cube segments. Such an approach permits a significant reduction of CPU and I/O overhead. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.
Poke: emotional touch delivery through an inflatable surface over interpersonal mobile communications

In this paper we present Poke - a soft and human-like re-mote touch technique through an inflatable surface. We aimed to design it for delivering more emotional and plea-sant touches over interpersonal mobile communications. Poke enables to touch human's skin with an inflatable sur-face according to the other user's finger pressures and hand gestures during a phone call. It delivers different kinds of pokes and other affective touches with its inflating patterns (strengths and repetitions) and vibrations from the top of the inflatable surface. The paper also suggests affective touches such as weak/hard poke, poke and then shake, poke back and pat which can be exchanged during typical phone calls.
Feature selection and allocation to diverse subsets for multi-label learning problems with large datasets

Feature selection is important phase in machine learning and in the case of multi-label classification, it can be considerably challenging. In like manner, finding the best subset of good features is involved and difficult when the dataset has significantly large number of features (more than a thousand). In this paper we address the problem of feature selection for multi-label classification with large number of features. The proposed method is a hybrid of two phases - preliminary feature selection based on the information value and additional correlation-based selection.We show how with the first phase we can do preliminary selection of features from tens of thousands to couple of hundred, and then with the second phase we can make fine-grained feature selection with more sophisticated but computationally intensive methods. Finally, we analyze the ways of allocating the selected features to diverse subsets, which are suitable for training of ensembles of classifiers.
Generalised phase kick-back: the structure of computational algorithms from physical principles

The advent of quantum computing has challenged classical conceptions of which problems are efficiently solvable in our physical world. This motivates the general study of how physical principles bound computational power. In this paper we show that some of the essential machinery of quantum computation—namely reversible controlled transformations and the phase kick-back mechanism—exist in any operational-defined theory with a consistent notion of information. These results provide the tools for an exploration of the physics underpinning the structure of computational algorithms. We investigate the relationship between interference behaviour and computational power, demonstrating that non-trivial interference behaviour is a general resource for post-classical computation. In proving the above, we connect higher-order interference to the existence of post-quantum particle types, potentially providing a novel experimental test for higher-order interference. Finally, we conjecture that theories with post-quantum interference—the higher-order interference of Sorkin—can solve problems intractable even on a quantum computer.
Breeding competitive strategies

We show how genetic algorithms can be used to evolve strategies in oligopolistic markets characterized by asymmetric competition. The approach is illustrated using scanner tracking data of brand actions in a real market. An asymmetric market-share model and a category-volume model are combined to represent market response to the actions of brand managers. The actions available to each artificial brand manager are constrained to four typical marketing actions of each from the historical data. Each brand's strategies evolve through simulations of repeated interactions in a virtual market, using the estimated weekly profits of each brand as measures of its fitness for the genetic algorithm. The artificial agents bred in this environment outperform the historical actions of brand managers in the real market. The implications of these findings for the study of marketing strategy are discussed.
Mechanism of Oxidation of Dimethyl Disulphide by Thiobacillus thioparus Strain E6

Summary: A recently isolated organism, capable of chemolithoautotrophic growth on dimethyl disulphide, was characterized as a strain of Thiobacillus thioparus. It had DNA with a base composition of 60.5 ± 1.0 mol% G + C, and ubiquinone-8 (UQ-8) as its only respiratory quinone. Its growth in chemostat culture (at a growth rate of 0.07-0.08 h−1) showed yields of 14.4, 11.8 and 2.45 g cell-carbon per mol of dimethyl disulphide (DMDS), dimethyl sulphide (DMS) and thiosulphate, respectively. This is consistent with energy generation from the oxidation of the methyl and the sulphide moieties of DMDS, with oxidation of sulphide to sulphate contributing a yield of about 2.8 g cell-carbon mol−1. From whole organism and cell-free extract studies, DMDS oxidation was shown to proceed by its (NADH-stimulated) reduction to methanethiol (MT), which was oxidized via sulphide, formaldehyde and formate to CO2 and sulphate by MT oxidase, formaldehyde and formate dehydrogenases, and an uncharacterized sulphide-oxidizing system. The MT oxidase had a K m of 9.7 μM and showed substrate inhibition with a K i of about 8 μM. The essential role of catalase during growth on DMDS was shown by the sensitivity of growth on DMDS (but not on thiosulphate) to 3-amino-1,2,4-triazole. Catalase is believed to destroy the peroxide produced by the MT oxidase reaction. DMDS-grown organisms oxidized sulphide, thiosulphate and tetrathionate (with the latter indicated to be an intermediate in thiosulphate oxidation), suggesting the pathway of sulphide oxidation to be similar to that in some other thiobacilli. Carbon assimilation was by the Calvin cycle, with ribulose bisphosphate carboxylase being present in cell-free extracts at a specific activity of 80 nmol CO2 fixed min−1 (mg protein)−1. Hydroxypyruvate reductase (HPR) was not detected at levels sufficient to indicate any role in primary carbon assimilation.
TCP/IP enhancements for satellite networks

With the emerging market for high-mobility remote access broadband services, satellite networks are becoming increasingly popular. Although the ubiquitous TCP/IP protocol is widely used to provide reliable data delivery in terrestrial networks, it faces many challenges in satellite environments. These stem from the inherent features of satellite channels, such as large delays, increased error rates, and bandwidth asymmetry. To address these concerns, a variety of solutions have been proposed. These include direct TCP enhancements to better tune the TCP/IP stack and additional selective acknowledgment mechanisms. Other proposals use advanced interworking to reduce sensitivity to various channel features. Examples include multiple TCP sessions, link-layer interworking, and ACK control schemes. Improving onboard satellite features (buffer management, flow control) can also provide benefits for TCP/IP transport. The objective of this article is to present the various solutions and discuss their possible trade-offs. Overall, there exists a rich set of alternatives to meet the challenges in this important arena.