Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of Circle women in curbing violence against women and girls in Africa

The article looks at the role Circle of Concerned African Women Theologians (the Circle) have played in the struggle to end or reduce the rate at which violence against women and girls occurs in West Africa by highlighting the contributions of older Circle women, especially the initiator of the Circle, Mercy Amba Oduyoye. The initiator of the Circle and other older Circle women have left a remarkable legacy that needs to continue by the current and future generations of the Circle. The background information examines the leadership and mentorship of Mercy Amba Oduyoye and the impact she has made in the lives of African women. The essay then looks at the types of violence that women face in West Africa with the specific contributions of Circle women in the struggle to end violence against women and girls. It then argues that Circle women have played very significant roles both in setting the pace and giving the platform for women activities to minimise gender-based violence against women and girls. Circle women have written and presented papers that have addressed many challenges including HIV and/or AIDS, Girl Child trafficking, Marriage of Minors, and almost all kinds of violence against women and girls. Currently, religious violence threatens the fabric of African nations causing insecurity and panic, women and girls being the most vulnerable. The challenge to the present and future Circle members is to contribute in significant ways towards religious harmony in Africa and beyond. The Circle acknowledges the leadership role of women and encourages them to spearhead the liberation of women as well as empower them to be able to aspire to get to the top or become independent. No one understands what someone else feels better than the person experiencing the ordeal. Women can better understand what they go through and also have the passion to strive towards liberation. Intradisciplinary and/or interdisciplinary implications: In this article, the discipline of practical theology combines with elements of social science and Gender Studies, bringing out the Circle’s contribution towards the eradication of religious and cultural and gender violence against women and girls in Ghana and Africa. Keywords: Circle; Theology; gender-based violence; Mercy Amba Oduyoye; West Africa
Robust language and speaker identification using image processing techniques combined with PCA

Spoken language and speaker identification has been attracting the researchers across the globe for past several decades. Language identification shares certain similarities with speaker identification; however they both differ from each other in certain aspects. Both language identification and speaker identification problems have till now been dealt with feature extraction techniques like MFCC, PLP, LPCC etc. In this paper, a new feature extraction technique is proposed. Radon transform (RT) is proposed to be used for feature extraction after obtaining the spectrogram from the speech sample. PCA has been used to achieve dimension reduction and to reduce the computational complexity. The performance of the proposed method has been compared for existing identification techniques in the field of language and speaker identification.
DCMR: A Method for Combining User-Based and Trust-Based Recommendation

Trust-based methods can recommend for cold-start users while collaborative filtering cannot, but collaborative fil- tering methods outperform in precision when recommending for the users with many ratings. In our approach, we combine these two kinds of methods in a novel way that exerts both of their advantages. Our combination method is a procedure of weight distribution and collection on predictors. It finds predictors by the breadth first search through the trust network. We present prediction confidence and trust attenuation as the two factors that affect weight distribution. Our experimental evaluation on the Epinions data set indicates that our method has a good performance.
Structure and function of cochlear afferent innervation

Purpose of reviewFor the perception of sound, acoustic signals need to be encoded into a neuronal code. This takes place at the inner hair cells of the organ of Corti and the afferent fibres of the auditory nerve. We will review the current knowledge of the anatomy and function of these elements as well as their connection – formed by the afferent inner hair cell synapse. Recent findingsDepending on their tonotopic location, inner hair cells are innervated by 5–30 dendrites of spiral ganglion neurons. Electrophysiological recordings from single fibres demonstrate – apart from a high-frequency selectivity – a pronounced heterogeneity in their response to sound of varying intensity. The source as well as the function of this heterogeneity is not well understood, but recent publications have suggested several mechanisms, including variations in the presynaptic Ca2+ influx and subsequent transmitter release, the postsynaptic sensitivity to neurotransmitter and electrical as well as anatomical variability of single fibres. These mechanisms might act together to expand the dynamic range of sound that can be encoded. SummaryClassical studies as well as recent publications demonstrate that sound encoding at the inner hair cell afferent synapse involves mechanisms leading to tonotopic frequency separation and distribution of intensity coding over many neuronal channels.
Performance of Multi-User Spatial Multiplexing with Measured Channel Data

The application of MIMO processing techniques in channels that are shared among multiple users is a relatively new problem that is increasingly important as MIMO transmission is put into practical use. In this chapter we specifically consider the multi-user downlink, where a base station with multiple antennas transmits simultaneously to more than one user. We begin with an overview of some of the multi-user MIMO transmission schemes that have been proposed up to this point, then demonstrate how they might be expected to perform by applying the algorithms to measurement data from indoor and outdoor propagation environments. Specifically, we compare the number of simultaneous users the channel will support for the two different environments, the amount of separation of the users necessary to achieve maximum throughput, and the quality of channel information available to the base station when the users are mobile. In both environments, full multi-user diversity is achieved at relatively short distances on the order of one meter. The total number of simultaneous users in outdoor environments is limited compared to uncorrelated channels due to the relatively sparse multipath structure of the channel. The distances at which channel information becomes too old to be useful to the transmitter appears to be similar for both types of channels.
Diagnosis of Switching Systems using Hybrid Bond Graph

Hybrid Bond Graph (HBG) is a Bond Graph-based modelling approach which provides an effective tool not only for dynamic modeling but also for fault detection and isolation (FDI) of switching systems. Bond graph (BG) has been proven useful for FDI for continuous systems. In addition, BG provides the causal relations between system’s variables which allow FDI algorithms to be developed systematically from the graph. There are many methods that exploit structural relations and functional redundancy in the system model to find efficient solutions for the residual generation and residual evaluation steps in FDI of switching systems. This paper describes two different techniques, quantitative and qualitative, based on common modelling approach that employs HBG. In quantitative approach, global analytical redundancy relationships (GARRs) are derived from the HBG model with a specified causality assignment procedure. GARRs describe the system behaviour at all of its operating modes. In qualitative approach, functional redundancy can be captured by a Temporal Causal Graph (TCG), a directed graph that may include temporal information.
Structural basis for the bacterial transcription-repair coupling factor/RNA polymerase interaction

The transcription-repair coupling factor (TRCF, the product of the mfd gene) is a widely conserved bacterial protein that mediates transcription-coupled DNA repair. TRCF uses its ATP-dependent DNA translocase activity to remove transcription complexes stalled at sites of DNA damage, and stimulates repair by recruiting components of the nucleotide excision repair pathway to the site. A protein/protein interaction between TRCF and the β-subunit of RNA polymerase (RNAP) is essential for TRCF function. CarD (also called CdnL), an essential regulator of rRNA transcription in Mycobacterium tuberculosis, shares a homologous RNAP interacting domain with TRCF and also interacts with the RNAP β-subunit. We determined the 2.9-Å resolution X-ray crystal structure of the RNAP interacting domain of TRCF complexed with the RNAP-β1 domain, which harbors the TRCF interaction determinants. The structure reveals details of the TRCF/RNAP protein/protein interface, providing a basis for the design and interpretation of experiments probing TRCF, and by homology CarD, function and interactions with the RNAP.
Effect design. Part 3: Oscillators: Sinusoidal and pseudonoise

In 1997, Jon Dattorro published articles entitled Effect Design that were to appear in the Journal in three parts. Parts 1 and 2 were published in the September and October issues. Part 3 is now being published, unedited. The paper is a tutorial intended to serve as a reference in the field of digital audio effects in the electronic music industry for those who are new to this specialization of digital signal processing. The effects presented are those that are demanded most often, hence they will serve as a good toolbox. The algorithms chosen are of such a fundamental nature that they will find application ubiquitously and often.
A three-stage framework for motorway travel time prediction

This paper presents a framework for short-term travel time prediction in a motorway with a three-stage architecture: traffic flow forecasting, traffic flow generation and travel time extraction. Traffic flow forecasting reads the historical traffic data and utilizes a forecasting model - Autoregressive Integrated Moving Average (ARIMA) to predict short-term traffic flow. The traffic flow generation utilizes the Cell Transmission Model (CTM) to generate outgoing flow of a road of interest based on the predicted incoming flow from ARIMA. Predicted short term travel times can then be obtained through N-Curve Analysis. Compared to most studies, this paper presents a historical data-driven framework for travel time prediction that can be trained based on specific profiles of routes and cities. The motorway M4 in Sydney, Australia was used to test this framework. It is shown that the predicted travel times can be used to anticipate congestion episodes at the network level.
Dynamic Monte Carlo radiation transfer in SPH: radiation pressure force implementation

We present a new framework for radiation hydrodynamics simulations. Gas dynamics is modelled by smoothed particle hydrodynamics (SPH), whereas radiation transfer is simulated via a time-dependent Monte Carlo approach that traces photon packets. As a first step in the development of the method, in this paper we consider the momentum transfer between radiation field and gas, which is important for systems where radiation pressure is high. There is no fundamental limitation on the number of radiation sources, the geometry or the optical depth of the problems that can be studied with the method. However, as expected for any Monte Carlo transfer scheme, stochastic noise presents a serious limitation. We present a number of tests that show that the errors of the method can be estimated accurately by considering Poisson noise fluctuations in the number of photon packets that SPH particles interact with per dynamical time. It is found that, for a reasonable accuracy, the momentum carried by photon packets must be much smaller than the typical momentum of SPH particles. We discuss numerical limitations of the code, and future steps that can be taken to improve performance and applicability of the method.
Efficient Scene Image Clustering for Internet Collections

This paper proposes an efficient approach to find clusters of spatially related scene images collected from the website. Our method firstly builds a guide table, in which the ranked results are given according to the relevance scores of image pairs obtained by the image retrieval methods. Then the image clusters are generated by repeatedly choosing a seed image and performing query expansion directed by the guide table. In the query process, feature matching is performed by using an affine invariant constraint which is presented to effectively reject outliers of the image feature correspondences. The proposed image clustering approach has been tested on the Bell Tower dataset consisting of more than 1K images which are collected from the photo-sharing website Flickr.com. The experimental results demonstrate the efficiency and effectiveness of our method.
G-Protein-Coupled Lysophosphatidic Acid Receptors and Their Regulation of AKT Signaling

A hallmark of G-protein-coupled receptors (GPCRs) is their ability to recognize and respond to chemically diverse ligands. Lysophospholipids constitute a relatively recent addition to these ligands and carry out their biological functions by activating G-proteins coupled to a large family of cell-surface receptors. This review aims to highlight salient features of cell signaling by one class of these receptors, known as lysophosphatidic acid (LPA) receptors, in the context of phosphatidylinositol 3-kinase (PI3K)–AKT pathway activation. LPA moieties efficiently activate AKT phosphorylation and activation in a multitude of cell types. The interplay between LPA, its receptors, the associated Gαi/o subunits, PI3K and AKT contributes to the regulation of cell survival, migration, proliferation and confers chemotherapy-resistance in certain cancers. However, detailed information on the regulation of PI3K–AKT signals induced by LPA receptors is missing from the literature. Here, some urgent issues for investigation are highlighted.
An investigation on performance of private enterprises social responsibility

Since China reformed and opened up to the world 30 years ago, private-owned enterprises have experienced an unprecedented development. Nowadays, there are many serious social problems in environment, ecology, employment, equity, etc. Under this circumstance, the general public has high expectations to private enterprises and asks them to undertake corporate social responsibilities. However, through the survey to the private enterprises in Jinan City of Shandong Province, we found that there are many deficiencies in the fulfillment of corporate social responsibility. For example, the sense of responsibility is weak; the employees lack legal rights; the private enterprises ignore the legitimate rights and interests of consumers; their contribution to community is inadequate. In view of this situation, this paper proposes a series of countermeasures to strengthen private corporate social responsibility
Necessity-matching approach for translated, rotated and scale characters recognition from Maps

This paper at first presents a novel approach to recognize characters, numbers or the signs under translation, scaling and rotation (TRS) from Civil Aerial Meteorological Maps by templates, which is based on a new class of moment invariants. Meanwhile, aiming to the important parameter (the range of orders for moment invariants) in it, we prove so that could decrease efficiently the errors brought by the absence or superabundance.
Potential of liraglutide in the treatment of patients with type 2 diabetes

Liraglutide is a long-acting analog of GLP-1, being developed by Novo Nordisk and currently undergoing regulatory review for the treatment of type 2 diabetes. Upon injection, liraglutide binds non-covalently to albumin, giving it a pharmacokinetic profile suitable for once-daily administration. In clinical trials of up to 1 year duration, liraglutide has been demonstrated to have beneficial effects on islet cell function, leading to improvements in glycemic control. Both fasting and postprandial glucose concentrations are lowered, and are associated with lasting reductions in HbA1c levels. Liraglutide is effective as monotherapy and in combination therapy with oral antidiabetic drugs, and reduces HbA1c by up to ∼1.5% from baseline (8.2%–8.4%). Because of the glucose-dependency of its action, there is a low incidence of hypoglycemia. Liraglutide is associated with body weight loss, and reductions in systolic blood pressure have been observed throughout the clinical trials. The most common adverse events reported with liraglutide are gastrointestinal (nausea, vomiting and diarrhea). These tend to be most pronounced during the initial period of therapy and decline with time. Further clinical experience with liraglutide will reveal its long-term durability, safety and efficacy.
Draft: Coherent Risk Measures

Part of the course was devoted to an analysis of Value at Risk and its relation to quantiles. A detailed discussion of this can be found in two papers by Artzner, Delbaen, Eber and Heath, ADEH1 and ADEH2. It will not be repeated here. We will rather concentrate on the mathematics behind the concept of coherent risk measures. They were introduced in the two mentioned papers and the mathematical theory was further developped in Delbaen (1999), D2. Further use of coherent risk measures can be found in the papers (and their references) by Jaschke, Ja and JaK, Tasche, AT and Föllmer-Schied, FS. The reader should consult the cited web-sites to find several papers dealing with this subject. The paper by Föllmer and Schied introduces a generalisation of coherent risk measures.
On the tracking performance of LMS and RLS algorithms in an adaptive MMSE CDMA receiver

This paper provides some analytical and experimental results in comparing the non-stationary tracking characteristics of LMS and RLS in multi-user detection. It is shown that under slow fading conditions, the LMS algorithm outperforms the RLS algorithm. In both cases, only the Doppler shift of the user of interest, but not that of the interference, affects the tracking performances
KAT‐5: Robust systems for autonomous vehicle navigation in challenging and unknown terrain

KAT‐5 was the fourth vehicle to make history in DARPA's 2005 Grand Challenge, where for the first time ever, autonomous vehicles were able to travel through 100 miles of rough terrain at average speeds greater than 15 mph. In this paper, we describe the mechanisms and methods that were used to develop the vehicle. We describe the main hardware systems with which the vehicle was outfitted for navigation, computing, and control. We describe the sensors, the computing grid, and the methods that controlled the navigation based on the sensor readings. We also discuss the experiences gained in the course of the development and provide highlights of actual field performance. © 2006 Wiley Periodicals, Inc.
Inkjet-printed dual microfluidic-based sensor integrated system

Demonstrated is a novel method to the fabrication of microfluidic devices utilizing a dual-sensor approach. The fabrication incorporates the use of poly(methyl-methacrylate) (PMMA) and inkjet-printing techniques. PMMA, a low-cost, robust material with low dielectric loss, is ideal for sensor fabrication. In addition, inkjet-printing polymer (SU-8) as a bonding layer dramatically improves the bonding strength and pressure handling. Furthermore, this system integrates two independent sensors in the same circuit, enabling concurrent calibration of two fluids. Based on the reaction in one sensor, response in another sensor for the same fluid can be predicted. The two sensors both have a sensitivity over 21 %/log(r) and a good independence in calibrating fluids. The sensor system works at microwave frequency, enabling applications in wireless sensing including various chemical analysis.
THE IMPLICATIONS OF GUNN–PETERSON TROUGHS IN THE He ii Lyα FOREST

Many experts believe that the z ∼ 3 He ii Lyα forest will suffer from the same saturation issues as the z ∼ 6 H i Lyα forest and, therefore, will not be a sensitive probe of He ii reionization. However, there are several factors that make He ii Lyα absorption more sensitive than H i Lyα. We show that observations of He ii Lyα and Lyβ Gunn–Peterson troughs can provide a relatively model-independent constraint on the volume-averaged He ii fraction of . This bound derives from first using the most underdense regions in the He ii forest to constrain the local He ii fraction and, then, assuming photoionization equilibrium with the maximum allowed photoionization rate to calculate the ionization state of nearby gas. It is possible to evade this constraint by a factor of ∼2, but only if the He ii were reionized recently. We argue that He ii Lyα Gunn–Peterson troughs observed in the spectra of Q0302−003 and HE2347−4342 signify the presence of ≳10 comoving Mpc patches in which 0.03$? >. This is a factor of 20 improvement over previous constraints from these spectra and 100 times stronger than the tightest constraint on the H i volume-filling fraction from the z > 6 H i Lyman forest.
A Speech Recognition System Based on Dynamic Characterization of Background Noise

Robustness of automatic speech recognition (ASR) systems in realistic conditions of background noise is the essential conditions for their ample diffusion. As we know, the systems which exist at present suffer, however, a notable decrease in performance in the presence of background noise. In this article we propose an ASR system based on a dynamic characterization of background noise. In particular, the system makes a dynamic choice of HMM model related to the different types of noise and corresponding to different signal to noise ratios (SNR). The system was implemented and the tests performed using the AURORA2 database. The results were compared with a nonadaptive classification system in the presence of clean conditions and 4 different types of background noise and with 6 different SNRs. The proposed ASR system was found to be particularly adapted to applications functioning in extremely noisy contexts