Miracle-dz/UniFAR-FTUs huggingface dataset:
Rethinking the Underclass: Future Directions in Southern African Labor History 1

Southern and South African labor history has, at least since the 1970s, been as much about the future of the region as about its past. Liberal scholars saw in apartheid and segregation irrational aberrations to the color-blind logic of capitalism. They believed the apartheid state to be an instrument of racial dominance but saw it as more or less neutral in terms of class relations. Economic growth and the abolishment of racial laws would bring freedom and equality—or at least equal opportunities. On the other hand, radical historians and sociologists thought of apartheid as a system that guaranteed the exploitation of cheap black labor for the benefit of capital. For them, apartheid was functional to capitalism.2 While both the liberal and the radical positions were often more nuanced than the other side would admit, the question that divided these two camps was one about politics and strategy: Would capitalist development bring an end to racial domination, or was it part of the problem? In the latter case, challenging apartheid and colonialism would also involve challenging capitalism. The vibrancy of these debates should continue to serve as an inspiration for labor historians. I will argue that for the Left to be able to formulate viable alternatives to present policies, we should look at the history and nature of labor and inequality in the region.
On the decidability of metric temporal logic

Metric temporal logic (MTL) is a prominent specification formalism for real-time systems. In this paper, we show that the satisfiability problem for MTL over finite timed words is decidable, with non-primitive recursive complexity. We also consider the model-checking problem for MTL: whether all words accepted by a given Alur-Dill timed automaton satisfy a given MTL formula. We show that this problem is decidable over finite words. Over infinite words, we show that model checking the safety fragment of MTL-which includes invariance and time-bounded response properties-is also decidable. These results are quite surprising in that they contradict various claims to the contrary that have appeared in the literature. The question of the decidability of MTL over infinite words remains open.
Molecular Analysis of Colletotrichum Species in the Carposphere and Phyllosphere of Olive

A metagenomic approach based on the use of genus specific primers was developed and utilized to characterize Colletotrichum species associated with the olive phyllosphere and carposphere. Selected markers enabled the specific amplification of almost the entire ITS1-5.8S-ITS2 region of the rDNA and its use as barcode gene. The analysis of different olive samples (green and senescent leaves, floral residues, symptomatic and asymptomatic fruits, and litter leaves and mummies) in three different phenological phases (June, October and December) enabled the detection of 12 genotypes associated with 4 phylotypes identified as C. godetiae, C. acutatum s.s. , C. gloeosporioides s.s. and C. kahawae. Another three genotypes were not identified at the level of species but were associated with the species complexes of C. acutatum, C. gloeosporioides and C. boninense sensu lato. Colletotrichum godetiae and C. acutatum s.s. were by far the most abundant while C. gloeosporioides s.s. was detected in a limited number of samples whereas ther phylotypes were rarely found. The high incidence of C. acutatum s.s. represents a novelty for Italy and more generally for the Mediterranean basin since it had been previously reported only in Portugal. As regards to the phenological phase, Colletotrichum species were found in a few samples in June and were diffused on all assessed samples in December. According to data new infections on olive tissues mainly occur in the late fall. Furthermore, Colletotrichum species seem to have a saprophytic behavior on floral olive residues. The method developed in the present study proved to be valuable and its future application may contribute to the study of cycle and aetiology of diseases caused by Colletotrichum species in many different pathosystems.
Type-changing rewriting and semantics-preserving transformation

We have identified a class of regular, whole-program transformations that cannot be safely performed with typical transformation techniques because transformation requires changing the types of terms. In these transformations, we want to change typically large parts of a program from using one type to using another type while simultaneously preserving the original program semantics after transformation. In this paper, we present type-and-transform systems, an automated approach to the whole-program transformation of terms involving type A to terms involving the isomorphic type B using type-changing rewrite rules. Type-and-transform systems establish typing and semantics relations between all source and target subprograms such that a complete transformation can guarantee the equivalent semantics of a whole program. We describe the type-and-transform system for the lambda calculus with let-polymorphism and general recursion, including several examples from the literature and properties of the system.
Structure Learning and Statistical Estimation in Distribution Networks - Part II

Limited placement of real-time monitoring devices in the distribution grid, recent trends notwithstanding, has prevented the easy implementation of demand-response and other smart grid applications. Part I of this paper discusses the problem of learning the operational structure of the grid from nodal voltage measurements. In this work (Part II), the learning of the operational radial structure is coupled with the problem of estimating nodal consumption statistics and inferring the line parameters in the grid. Based on a Linear-Coupled(LC) approximation of AC power flows equations, polynomial time algorithms are designed to identify the structure and estimate nodal load characteristics and/or line parameters in the grid using the available nodal voltage measurements. Then the structure learning algorithm is extended to cases with missing data, where available observations are limited to a fraction of the grid nodes. The efficacy of the presented algorithms are demonstrated through simulations on several distribution test cases.
A fast and robust head pose estimation system based on depth data

This paper proposes a performance enhancement algorithm for Kinect depth data based head pose estimation method that uses discriminative random regression forest (DRRF). In the testing phase of DRRF, patches are extracted from the whole query depth image and then are passed through each of the tree in the trained forest for head detection and head pose estimation. In this procedure, however, errors in head detection may occur when some complex background information appears in the depth image. Moreover, the more background information the depth image contains, the more processing time is required. Another drawback of DRRF is that it is very sensitive in live mode. For example, the measurement of head pose may vibrate heavily even the pose of the head stays unchanged. In this paper, we present an improved algorithm by combining DRRF with Kalman filter. The new algorithm has greatly improved the reliability for head pose estimation. In this approach, the head location is first predicted using Kalman filter, and then patches are extracted from the head region defined by the predicted head location. The head pose is then estimated by passing these patches through DRRF for regression. Finally, the noisy regression result is refined by the correcting model of Kalman filter. Experimental results show that the proposed algorithm is faster, more robust and more accurate than the original DRRF.
Dietary Beliefs and Behavior Among Inflammatory Bowel Disease Patients

Background:We investigated dietary beliefs and behavior in a large population of adult inflammatory bowel disease (IBD) patients and evaluated their impact on patients' social life. Methods:A questionnaire of 14 items was administered to all consecutive IBD patients followed at the Nancy University Hospital Department of Gastroenterology from February to July 2011. Results:A total of 244 patients participated in the survey; 15.6% (n = 38) of patients believed that diet could initiate the disease, while 57.8% (n = 141) believed that food can play a role in causing a relapse. Forty percent (107/244) of patients identified food as a risk factor for relapse. Seventy-three percent of respondents reported having already received nutritional advice. The majority of respondents (47.5%, n = 116) reported that the disease had changed the pleasure of eating. Only one-quarter of patients had a normal diet in case of relapse. Almost two out of three patients (66.8%, n = 163) reported not eating certain foods they usually like to eat in order to prevent a relapse. Dietary beliefs and behavior had an impact on their social life for one-fifth of patients. Excluding food was associated with refusing outdoor dining for fear of causing relapse (P = 0.006) and not sharing the same menu as the other members of the family living under the same roof (P = 0.002). Conclusions:The majority of IBD patients are avoiding certain foods. Dietary beliefs and behavior have a strong impact on their social life.
Managing emotions. Accenting the positive might not produce the highest satisfaction payoff.

The relationship between patient emotions during hospitalization and their retrospective satisfaction varies across service elements, across emotions, and is influenced by the temporal positioning of both emotions and the service element. Marketers should concentrate on reducing negative emotions attributed to the provider (e.g., hostility and frustration) and to the hospitalization situation (e.g., distress and depression), according to the results of the authors' study. Providers also should attempt to alleviate negative emotional states connected with arousal (e.g., jittery and excited). Positive emotions were found to be only weakly related to satisfaction. The authors suggest segmenting patients on the basis of their emotional states at particular junctures of the service delivery and then "socializing" both providers and patients to ensure successful emotion management.
Streptolysin O Rapidly Impairs Neutrophil Oxidative Burst and Antibacterial Responses to Group A Streptococcus

Group A Streptococcus (GAS) causes a wide range of human infections, ranging from simple pharyngitis to life-threatening necrotizing fasciitis and toxic shock syndrome. A globally disseminated clone of M1T1 GAS has been associated with an increase in severe, invasive GAS infections in recent decades. The secreted GAS pore-forming toxin streptolysin O (SLO), which induces eukaryotic cell lysis in a cholesterol-dependent manner, is highly upregulated in the GAS M1T1 clone during bloodstream dissemination. SLO is known to promote GAS resistance to phagocytic clearance by neutrophils, a critical first element of host defense against invasive bacterial infection. Here, we examine the role of SLO in modulating specific neutrophil functions during their early interaction with GAS. We find that SLO at subcytotoxic concentrations and early time points is necessary and sufficient to suppress neutrophil oxidative burst, in a manner reversed by free cholesterol and anti-SLO blocking antibodies. In addition, SLO at subcytotoxic concentrations blocked neutrophil degranulation, interleukin-8 secretion and responsiveness, and elaboration of DNA-based neutrophil extracellular traps, cumulatively supporting a key role for SLO in GAS resistance to immediate neutrophil killing. A non-toxic SLO derivate elicits protective immunity against lethal GAS challenge in a murine infection model. We conclude that SLO exerts a novel cytotoxic-independent function at early stages of invasive infections (<30 min), contributing to GAS escape from neutrophil clearance.
Improved distributed automatic target recognition performance via spatial diversity and data fusion

Radar target classification is examined from the viewpoint of improving classification performance through the use of spatial diversity. Improved radar target classification has been demonstrated previously by using at least one additional perspective in a generic environment but the impact of sensor placement has been less studied. In this paper, we examine the use of multiple high range resolution (HRR) profiles to demonstrate how selection of sensor locations can improve classification rates. Specifically, performance improvements are demonstrated after identifying the optimal set of perspectives and employing a simple decision fusion network (DFN) algorithm for defined signal-to-noise (SNR) levels. We show percentages of correct classification (PCC) can be maintained in scenarios where SNR has been reduced by up to 9 dB on a single sensor basis.
Visible light alters yeast metabolic rhythms by inhibiting respiration

Significance In some organisms, respiration fluctuates cyclically, and these rhythms can be a sensitive gauge of metabolism. Constant or pulsatile exposure of yeast to visible wavelengths of light significantly alters and/or initiates these respiratory oscillations, revealing a further dimension of the challenges to yeast living in natural environments. Our results also have implications for the use of light as research tools—e.g., for excitation of fluorescence microscopically—even in organisms such as yeast that do not express specialized photoreceptive molecules. Moreover, the growth of yeast strains that are null for the yeast activator protein-1 gene that regulates oxidative stress genes is exquisitely sensitive to visible light, indicating that light can both modulate respiration and induce oxidative stress. Exposure of cells to visible light in nature or in fluorescence microscopy often is considered to be relatively innocuous. However, using the yeast respiratory oscillation (YRO) as a sensitive measurement of metabolism, we find that non-UV visible light has a significant impact on yeast metabolism. Blue/green wavelengths of visible light shorten the period and dampen the amplitude of the YRO, which is an ultradian rhythm of cell metabolism and transcription. The wavelengths of light that have the greatest effect coincide with the peak absorption regions of cytochromes. Moreover, treating yeast with the electron transport inhibitor sodium azide has similar effects on the YRO as visible light. Because impairment of respiration by light would change several state variables believed to play vital roles in the YRO (e.g., oxygen tension and ATP levels), we tested oxygen’s role in YRO stability and found that externally induced oxygen depletion can reset the phase of the oscillation, demonstrating that respiratory capacity plays a role in the oscillation’s period and phase. Light-induced damage to the cytochromes also produces reactive oxygen species that up-regulate the oxidative stress response gene TRX2 that is involved in pathways that enable sustained growth in bright visible light. Therefore, visible light can modulate cellular rhythmicity and metabolism through unexpectedly photosensitive pathways.
Covering Muslim women: Semantic macrostructures in BBC News

Despite a proliferation of research on Islam and Muslims in the media, very little work has focused on Muslim women, a much-debated social group that merits special consideration. This article aims to investigate how Muslim women are represented in BBC News website texts using a purpose-built corpus (1.9 million words in 3269 articles). The research employs analytical tools from the discourse-historical, socio-cognitive, and sociosemantic approaches to critical discourse studies. These are combined with corpus-based methodologies to investigate the semantic macrostructures that tend to be associated with Muslim women and the discursive strategies employed in the representation of the hijab. The study is novel in its exhaustive approach to identifying salient and underreported issues related to Muslim women in news discourse. It also introduces a more integrated analysis that combines manual and automated techniques and tackles the quantification of qualitative results where possible. Findings suggest that Muslim women’s representations are largely restricted in terms of regional coverage. Semantic macrostructures related to conflict and crime are prevalent. The hijab remains a nodal discourse surrounding Muslim women whose function as a descriptive feature is often unclear, raising serious questions about its relevance. A number of recommendations are made for journalists to become cognizant of their own context models when reporting on Muslim women.
A two-step approach to hallucinating faces: global parametric model and local nonparametric model

In this paper, we study face hallucination, or synthesizing a high-resolution face image from low-resolution input, with the help of a large collection of high-resolution face images. We develop a two-step statistical modeling approach that integrates both a global parametric model and a local nonparametric model. First, we derive a global linear model to learn the relationship between the high-resolution face images and their smoothed and down-sampled lower resolution ones. Second, the residual between an original high-resolution image and the reconstructed high-resolution image by a learned linear model is modeled by a patch-based nonparametric Markov network, to capture the high-frequency content of faces. By integrating both global and local models, we can generate photorealistic face images. Our approach is demonstrated by extensive experiments with high-quality hallucinated faces.
TRANSDUCTION IN BACILLUS SUBTILIS

Thorne, Curtis B. (Fort Detrick, Frederick, Md.). Transduction in Bacillus subtilis. J. Bacteriol. 83:106–111. 1962. —A bacteriophage, SP-10, isolated from soil carries out general transduction in Bacillus subtilis. Phage propagated on a streptomycin-resistant mutant of the wild-type strain W-23 was capable of transducing to prototrophy strain 168 (indole–), as well as all of the auxotrophic mutants of W-23-Sr tested, which included mutants requiring arginine, histidine, adenine, guanine, thiamine, leucine, or methionine. Although strain 168 was transduced by phage SP-10, lytic activity on this strain could not be detected and attempts to propagate the phage on it failed. Transductions occurred at frequencies in the range of 10-6 to 10-5 per plaque-forming unit. Homologous phage was ineffective, deoxyribonuclease had no effect on the frequency of transduction, and transduction was prevented by the addition of phage antiserum. Phage SP-10 was capable of lysogenizing strain W-23-Sr, and this condition was maintained through repeated growth and sporulation cycles in potato-extract medium. Although heating at 65 C for 60 min inactivated free phage particles, spores retained their lysogenic condition after such heat treatment. When heat-treated spores of the lysogenic cultures were used as inocula for growth in a nutrient broth-yeast extract-glucose medium, filtrates contained 109, or more, phage particles per ml.
A method for fast encoder‐free mapping in unstructured environments

The primary purpose of rescue robots is to locate victims within a disaster environment, either to report their position or to deliver aid. Although there exist several solutions for mapping and localizing a robot in an unknown environment, they often require an estimate of the robot's motion. In a disaster site, a robot might not have effective motion encoders, either because of the discontinuous nature of the terrain or because the robot's locomotion devices do not remain in constant contact with the ground. We have developed an algorithm for tracking the position of a robot in a disaster environment and generating a map that functions in real time. Our solution is based on a range finder device and is robust to temporary errors in the range scan. By aligning each scan to an occupancy grid of prior scan data, we can find the robot's position more accurately than current techniques that align only to the previous scan. The accurate position tracking allows us to more efficiently implement a solution to the mapping problem. In addition, our solution can track the position of the robot and generate a map based on three‐dimensional scan data, instead of requiring that the range sensor be fixed in a level plane. © 2011 Wiley Periodicals, Inc.
A Combination of Off-line and On-line Learning to Classifier Grids for Object Detection

We propose a new method for object detection by combining off-line and on-line boosting learning to classifier grids based on visual information without human intervention concerned to intelligent surveillance system. It allows for combine information labeled and unlabeled use different contexts to update the system, which is not available at off-line training time. The main goal is to develop an adaptive but robust system and to combine prior knowledge with new information in an unsupervised learning framework that is learning 24 hours a day and 7 days a week. We use co-training strategy by combining off-line and on-line learning to the classifier grids. The proposed method is practically favorable as it meets the requirements of real-time performance, accuracy and robustness. It works well with reasonable amount of training samples and is computational efficiency. Experiments on detection of objects in challenging data sets show the outperforming of our approach.
Simple approach for the preparation of 15−15N2-enriched water for nitrogen fixation assessments: evaluation, application and recommendations

Recent findings revealed that the commonly used 15N2 tracer assay for the determination of dinitrogen (N2) fixation can underestimate the activity of aquatic N2-fixing organisms. Therefore, a modification to the method using pre-prepared 15−15N2-enriched water was proposed. Here, we present a rigorous assessment and outline a simple procedure for the preparation of 15−15N2-enriched water. We recommend to fill sterile-filtered water into serum bottles and to add 15−15N2 gas to the water in amounts exceeding the standard N2 solubility, followed by vigorous agitation (vortex mixing ≥ 5 min). Optionally, water can be degassed at low-pressure (≥950 mbar) for 10 min prior to the 15−15N2 gas addition to indirectly enhance the 15−15N2 concentration. This preparation of 15−15N2-enriched water can be done within 1 h using standard laboratory equipment. The final 15N-atom% excess was 5% after replacing 2–5% of the incubation volume with 15−15N2-enriched water. Notably, the addition of 15−15N2-enriched water can alter levels of trace elements in the incubation water due to the contact of 15−15N2-enriched water with glass, plastic and rubber ware. In our tests, levels of trace elements (Fe, P, Mn, Mo, Cu, Zn) increased by up to 0.1 nmol L−1 in the final incubation volume, which may bias rate measurements in regions where N2 fixation is limited by trace elements. For these regions, we tested an alternative way to enrich water with 15−15N2. The 15−15N2 was injected as a bubble directly to the incubation water, followed by gentle shaking. Immediately thereafter, the bubble was replaced with water to stop the 15−15N2 equilibration. This approach achieved a 15N-atom% excess of 6.6 ± 1.7% when adding 2 mL 15−15N2 per liter of incubation water. The herein presented methodological tests offer guidelines for the 15N2 tracer assay and thus, are crucial to circumvent methodological draw-backs for future N2 fixation assessments.