Miracle-dz/UniFAR-FTUs huggingface dataset:
Alchemies of Altruism: Motivations and Opportunities in the Rescue of Jews in Nazi Europe

This paper seeks to explore the underlying mechanisms of altruistic behaviour – a topic dominated by experimental studies, mainly in the field of psychology. This paper expands our understandings of the processes that impinge on such behaviour by focusing on a ‘naturalistic’ study of altruism in a high-risk situation. It thus concentrates on the rescue of persecuted Jews in the Holocaust. In explaining altruistic behaviour it is common to make a distinction between the effect of situational factors and the effect of motivational factors. Applying a case control sample technique to the analysis of the APPBI data on those who rescued Jews and those who did not rescue Jews during the Nazi occupation of Europe (N=510), we show that situational factors (a direct request for help) substantially increase the likelihood of a Jew to be rescued. We further show that motivational factors (defined in this study as a ‘prosocial action orientation’) are important too in arriving at altruistic behaviour. However, we also show that motivational and situational factors interact in generating altruistic behaviour. Thus, we conclude, in arriving at altruistic behaviour situational factors may be seen to activate motivational factors. Finally, utilizing nonparametric techniques to the analysis of the APPBI data, we were able to rule out the hypothesis that this activation process (i.e., the interaction effect) is governed by a threshold effect. We show, instead, that this process is linear. A discussion of the implications of this study concludes the paper.
Redetermination of MgTe2O5

The crystal structure of the title compound, magnesium penta­oxoditellurate(IV), has been redetermined from a crystal grown from the melt and confirms the previous study [Tromel (1975). Z. Anorg. Allg. Chem. 418, 141–144], but with improved precision. It is isotypic with β-MnTe2O5 and contains MgO6 octa­hedra and TeO3+1 units, with the latter forming an extended sheet structure. Mg and one O atom occupy special positions with site symmetry 2.
A new subspecies of microsnail from Masungi Georeserve, Rizal, Philippines

A new subspecies of microsnail, Hypselostoma latispira masungiensis subsp. nov., is described based on shell morphology and molecular characters. This new subspecies is distinguished from H. l. latispira from Baguio City, Benguet Province by having relatively larger major width size, additional apertural teeth (interpalatal plica), larger body whorl and apertural width, and clustering based on location. The collected samples from Masungi Georeserve, Rizal Province appear to be an ecophenotype as indicated by the novel site congruent to the clade separation of Masungi and Baguio H. latispira. Neighbor-joining and maximum likelihood trees also demonstrated that the two sample groups clustered separately, with bootstrap support of 84% and 78%, respectively. However, pairwise distance comparison revealed that there is only an average of 0.0131 ± 0.0126 genetic distance (99.98%) between the two populations, suggesting that they are most likely similar species; thus, the proposal of making it a subspecies. This is the first report on the new distributional record outside the type locality and a new subspecies of H. latispira. KEYWORDS: land snail, karst, interpalatal plica, pairwise distance comparison
Running head: NURSE TO PATIENT RATIOS AND THE EFFECTS ON PATIENT 1 Nurse to Patient Ratios and the Effects on Patient Outcomes: An Evidence Based Practice Analysis

Evidenced based research has shown an unequivocal relationship between minimal nurse to patient ratios and increases in adverse effects on patient outcomes in the hospital setting. Staffing ratios and patient outcomes can be positively affected by not only number of staff but also, those that are fulltime employees, their skill set and educational level, as well as available resources. The importance of executing an increased nurse to patient ratios in union represented hospitals and a Magnet status hospital has positive patient outcomes and safety and psychologically, a positive nurse experience.
Earnings Management during Mergers and Acquisitions – European Evidence

This study examines the behavior of European listed and non-listed firms in terms of earnings management practices. The sample is composed by 409 acquirers which have announced and completed M&A deals between 2009 and 2016. From the 409 completed transactions, 29% of them concern stock payments against 71% of them that concern cash payments. The accruals were estimated via the modified version of Jones model in order to obtain the component of discretionary accruals, the main proxy for earnings management. The tested sample considered 400 acquirers combined with the respective 400 matching firms that have not participated in M&A deals during the sample period. The results provide weak evidence that managers manipulate earnings upwards in the period prior to their M&A announcements. These findings seem to approach those of Erickson & Wang (1999) and Koumanakos et al. (2005) for which pre-merger earnings were not managed by cash acquirers.
esistance to thiabendazole and baseline sensitivity to fludioxonil and yrimethanil in Botrytis cinerea populations from apple and ear in Washington State

Gray mold caused by Botrytis cinerea is a common postharvest disease of pome fruit. Thiabendazole was the most commonly used postharvest fungicide prior to the registration of fludioxonil and pyrimethanil in 2004 for postharvest use on pome fruit. In this study, 83 and 40 isolates of B. cinerea that had not been exposed to fludioxonil and pyrimethanil were obtained from apple and pear, respectively, screened for resistance to thiabendazole, and tested for sensitivity to fludioxonil and pyrimethanil. Three isolates from apple were highly resistant to thiabendazole, while all remaining isolates were sensitive to thiabendazole. EC50 values of fludioxonil ranged from 0.003 to 0.038 (mean = 0.005) mg/L for apple isolates and from 0.003 to 0.008 (mean = 0.005) mg/L for pear isolates. EC50 values of pyrimethanil ranged from 0.013 to 0.173 (mean = 0.060) mg/L and from 0.015 to 0.117 (mean = 0.048) mg/L for apple and pear isolates, respectively. One apple isolate exhibited reduced sensitivity to fludioxonil with EC50 of 0.038 mg/L, which was significantly higher than those of remaining isolates tested and was considered resistant to fludioxonil. After 20 successive generations on potato dextrose agar and four generations on apple fruit, the fludioxonil-resistant isolate retained the same level of resistance to fludioxonil as the initial generation. However, it showed a higher sensitivity to osmotic stress in vitro, was less pathogenic and virulent on apple fruit, and produced fewer conidia in vivo at 0 ◦C than fludioxonil-sensitive isolates. On apple fruit at 0 ◦C, the fludioxonil-resistant isolate was effectively controlled by thiabendazole and pyrimethanil but only partially controlled by fludioxonil. The results indicate that insensitivity to fludioxonil was present in a non-fludioxonil-exposed population of B. cinerea from pome fruit in the region but at a low frequency and that the vast majority of isolates in the baseline population of B. cinerea from pome fruit in the region were sensitive to and can be effectively controlled by the two newly registered postharvest fungicides.
Tafoni formation at Theologos

The aim of this paper is to provide further information of the tafoni development. At Theologos area, Fthiotis Prefecture, north Euboean Gulf, a carbonate formation hosts a variety of well developed tafoni. 165 tafoni were, randomly, selected by means of a detailed geomorphological investigation. The presence or absence of lichen cover, rock flaking, and cavern floor debris, amalgamation, salt flakes, different kind of structures, biological communities, were noted, while measurements regarding their dimension took place. Surface hardness values, obtained using a Schmidt hammer. Although, there is no evidence of the key factor that drives the growth of tafoni, salt weathering and low strength seems determinant of their formation. Moreover, much of the evidences suggest that joints are actively influencing the origin and the morphology of tafoni. It is possible that tafoni formation is initiated at weak zones. Τhe studied tafoni are actively developing and are not relict features inherited from a past environment. It seems that their evolutionary stage is II towards to III. The results of chemical and mineralogical analysis indicate that during the cavernous weathering, silica, sulphates, alumina and iron oxides have replaced carbonate grains. Also, at the non-weathered part of the rock, the main mineralogical phases are calcite and doplomite.
NEUROPLASTICITY, GENRE, AND IDENTITY: POSSIBILITIES AND COMPLICATIONS1

In Connectome: How the Brain’s Wiring Makes Us How We Are, Sebastian Seung (2011) maintains that what is usually considered “identity” is strongly linked to “the totality of connections between the neurons in a nervous system,” (p. xiii), a phenomenon that he defines as a “connectome. ” Seung argues that “minds differ because connectomes differ” (2011, p. xiv), and that a person’s “connectomes change throughout life” (p. xv), influenced by many factors, including skill acquisition, new knowledge, and life events. The concept of a connectome suggests that identity has a physical manifestation that can be discerned in neuronal activities, and that because these activities are perpetually in flux, the concept of identity should not be viewed as an essentialized, permanently etched static construct, but rather as a complex state of being that is subject to change. Moreover, it further suggests that because neuronal activity is activated by experiences, activities, and learning, “identity” can be influenced by performative elements, over which, at least potentially, the conscious performer can have agency. What are the implications of this perspective on identity for Writing Studies scholarship? In this chapter, I will argue that current research in neuroplasticity—that is, changes in the brain that can occur through education and experience—problematizes the idea of an “authentic” identity and the extent to
Serological and Molecular Comparison Study for Diagnosis of Cytomegalovirus Infection in aborted Pregnant Women in Iraq

This study was conducted to investigate the Cytomegalovirus (CMV) infections of pregnant women. The samples were collected from Mosul and Baghdad hospitals in Iraq for two years and the tested women within the age category of under 20 to above 39 years. One thousand five hundred samples were taken as serum, to use in ELISA (IgM, IgG). EDTA blood, Heparin blood and cervical swabs were used in molecular tests. Three hundred positive samples demonstrating the presence of IgM and IgG antibodies using ELISA test. IgM antibodies were positive in 146 (48.7%) CMV, IgG antibodies were positive in 189 (63%) for CMV. DNA was extracted and Real-Time PCR indicates positive in only four samples (1.3%) in CMV from all 300 positive samples in ELISA tests.
INVESTIGATION OF INFORMATION IMPACT ON OVERCOMING CONSUMER RESISTANCE TO ACCEPT MOBILE BANKING PROVIDED BY MELLI BANK OF IRAN

The purpose of this paper is to investigate the impact of information and guidance offered by the bank on two types of consumers’ resistance i.e. functional and psychological resistances in adoption of mobile banking provided by Melli Bank of Iran. According to the purpose, five hypotheses are developed and tested. It is noteworthy that the present research is classified as a casual research based on its nature and methodology; with regard to its implementation method, it is known as a survey and according to purpose, it is an applied research in which the Structural Equation Modeling (SEM) is employed to examine the relationships between components of the proposed model. The research sample includes the users of mobile banking provided by Melli Bank of Iran during 2010-2011. In order to achieve the research objectives, 240 questionnaires were distributed among the users of mobile banking provided by Melli Bank of Iran in the city of Arak, Markazi province, from which 204 questionnaires were analyzed. After data analysis, all of the proposed research hypotheses were confirmed. The research results show that the information and guidance provided by the Melli Bank of Iran have been effective in reducing psychological and functional barriers and the highest impact has been obtained for image and tradition barriers.
Macroeconomic implications of Eurobonds

Member states of the euro area disagree o v r proposals for issuing common sovereign bonds (Eurobonds) with full joint liability. Some o f them fear that heavy indebted countries will no longer care about fiscal discipline once Eu robonds are implemented. We build a twocountry monetary union DSGE model to compare three sc narios of government debt issuance: National bonds, Eurobonds, and Limited Eurobonds (a cap on the issuance of Eurobonds). Assuming that a country decides to increase public spending and cares little about debt stabilization, we find that its spending multiplier would be the highest with Eurobonds and the lowest with Limited Eurobonds. The spillover effect s on output in the rest of the union would be negative with Eurobonds but positive with Limite d Eurobonds. Our findings hence support the case for limited joint liability.
Influence of pelleted browse-based supplements fed with a basal diet of Andropogon gayanus hay on intake, digestibility, growth and haemato-biochemical indices in West African Dwarf goat

This study evaluated the nutritional value of pelleted supplements based on four major feed resources fed to small ruminants by smallholder farmers in the Accra Plains. Leaves of Samanea saman, Acacia auriculiformis and Ficus exasperata, and cassava peels were dried, milled, mixed with other ingredients and pelleted to form Samanea saman (SS-S), Acacia auriculiformis (AA-S), Ficus exasperata (FE-S) and cassava peel (CP-S) based supplements. The supplements were fed to twenty West African Dwarf goats on a basal diet of Andropogon gayanus (Gamba grass) hay in a completely randomised design experiment. Voluntary intake of dry matter did not differ (P>0.05) by the type of supplement. However, crude protein intake was higher (P<0.05) in goats fed FE-S than those fed CP-S. Acid detergent fibre intake was higher (P<0.05) for SS-S, AA-S and FE-S than CP-S. Digestibility of dry matter, organic matter, crude protein, acid detergent fibre and neutral detergent fibre were lowest (P<0.05) for goats on CP-S. Average daily weight gain and Feed conversion ratio were not affected (P>0.05) by dietary treatments. Also, dietary treatment did not affect (P>0.05) the concentrations haematological and blood biochemical constituents determined except urea which was higher (P<0.05) in goats fed SS-S than the other treatments. In conclusion, the above results suggest that browse-based and cassava peel-based supplements could be fed to confined goats on roughage diets especially in the dry season without any deleterious effects on intake, growth and physiology of goats.
Federated Composite Optimization

Federated Learning (FL) is a distributed learning paradigm which scales on-device learning collaboratively and privately. Standard FL algorithms such as Federated Averaging (FedAvg) are primarily geared towards smooth unconstrained settings. In this paper, we study the Federated Composite Optimization (FCO) problem, where the objective function in FL includes an additive (possibly) non-smooth component. Such optimization problems are fundamental to machine learning and arise naturally in the context of regularization (e.g., sparsity, low-rank, monotonicity, and constraint). To tackle this problem, we propose different primal/dual averaging approaches and study their communication and computation complexities. Of particular interest is Federated Dual Averaging (FedDualAvg), a federated variant of the dual averaging algorithm. FedDualAvg uses a novel double averaging procedure, which involves gradient averaging step in standard dual averaging and an average of client updates akin to standard federated averaging. Our theoretical analysis and empirical experiments demonstrate that FedDualAvg outperforms baselines for FCO.
Facebook AI’s WMT20 News Translation Task Submission

This paper describes Facebook AI’s submission to WMT20 shared news translation task. We focus on the low resource setting and participate in two language pairs, Tamil <-> English and Inuktitut <-> English, where there are limited out-of-domain bitext and monolingual data. We approach the low resource problem using two main strategies, leveraging all available data and adapting the system to the target news domain. We explore techniques that leverage bitext and monolingual data from all languages, such as self-supervised model pretraining, multilingual models, data augmentation, and reranking. To better adapt the translation system to the test domain, we explore dataset tagging and fine-tuning on in-domain data. We observe that different techniques provide varied improvements based on the available data of the language pair. Based on the finding, we integrate these techniques into one training pipeline. For En->Ta, we explore an unconstrained setup with additional Tamil bitext and monolingual data and show that further improvement can be obtained. On the test set, our best submitted systems achieve 21.5 and 13.7 BLEU for Ta->En and En->Ta respectively, and 27.9 and 13.0 for Iu->En and En->Iu respectively.
Neural Semi-supervised Learning for Text Classification Under Large-Scale Pretraining

The goal of semi-supervised learning is to utilize the unlabeled, in-domain dataset U to improve models trained on the labeled dataset D. Under the context of large-scale language-model (LM) pretraining, how we can make the best use of U is poorly understood: is semi-supervised learning still beneficial with the presence of large-scale pretraining? should U be used for in-domain LM pretraining or pseudo-label generation? how should the pseudo-label based semi-supervised model be actually implemented? how different semi-supervised strategies affect performances regarding D of different sizes, U of different sizes, etc. In this paper, we conduct comprehensive studies on semi-supervised learning in the task of text classification under the context of large-scale LM pretraining. Our studies shed important lights on the behavior of semi-supervised learning methods: (1) with the presence of in-domain pretraining LM on U, open-domain LM pretraining is unnecessary; (2) both the in-domain pretraining strategy and the pseudo-label based strategy introduce significant performance boosts, with the former performing better with larger U, the latter performing better with smaller U, and the combination leading to the largest performance boost; (3) self-training (pretraining first on pseudo labels D' and then fine-tuning on D) yields better performances when D is small, while joint training on the combination of pseudo labels D' and the original dataset D yields better performances when D is large. Using semi-supervised learning strategies, we are able to achieve a performance of around 93.8% accuracy with only 50 training data points on the IMDB dataset, and a competitive performance of 96.6% with the full IMDB dataset. Our work marks an initial step in understanding the behavior of semi-supervised learning models under the context of large-scale pretraining.
A Divide et Impera Approach for 3D Shape Reconstruction from Multiple Views

Estimating the 3D shape of an object from a single or multiple images has gained popularity thanks to the recent breakthroughs powered by deep learning. Most approaches regress the full object shape in a canonical pose, possibly extrapolating the occluded parts based on the learned priors. However, their viewpoint invariant technique often discards the unique structures visible from the input images. In contrast, this paper proposes to rely on viewpoint variant reconstructions by merging the visible information from the given views. Our approach is divided into three steps. Starting from the sparse views of the object, we first align them into a common coordinate system by estimating the relative pose between all the pairs. Then, inspired by the traditional voxel carving, we generate an occupancy grid of the object taken from the silhouette on the images and their relative poses. Finally, we refine the initial reconstruction to build a clean 3D model which preserves the details from each viewpoint. To validate the proposed method, we perform a comprehensive evaluation on the ShapeNet reference benchmark in terms of relative pose estimation and 3D shape reconstruction.
Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder

Identification of the type of communication technology and/or modulation scheme based on detected radio signal are challenging problems encountered in a variety of applications including spectrum allocation and radio interference mitigation. They are rendered difficult due to a growing number of emitter types and varied effects of real-world channels upon the radio signal. Existing spectrum monitoring techniques are capable of acquiring massive amounts of radio and real-time spectrum data using compact sensors deployed in a variety of settings. However, state-of-the-art methods that use such data to classify emitter types and detect communication schemes struggle to achieve required levels of accuracy at a computational efficiency that would allow their implementation on low-cost computational platforms. In this paper, we present a learning framework based on an LSTM denoising auto-encoder designed to automatically extract stable and robust features from noisy radio signals, and infer modulation or technology type using the learned features. The algorithm utilizes a compact neural network architecture readily implemented on a low-cost computational platform while exceeding state-of-the-art accuracy. Results on realistic synthetic as well as over-the-air radio data demonstrate that the proposed framework reliably and efficiently classifies received radio signals, often demonstrating superior performance compared to state-of-the-art methods. Source codes are available at https://github.com/WuLoli/LSTMDAE.
Slender Object Detection: Diagnoses and Improvements

In this paper, we are concerned with the detection of a particular type of objects with extreme aspect ratios, namely slender objects. In real-world scenarios as well as widely-used datasets (such as COCO), slender objects are actually very common. However, this type of object has been largely overlooked by previous object detection algorithms. Upon our investigation, for a classical object detection method, a drastic drop of 18.9% mAP on COCO is observed, if solely evaluated on slender objects. Therefore, We systematically study the problem of slender object detection in this work. Accordingly, an analytical framework with carefully designed benchmark and evaluation protocols is established, in which different algorithms and modules can be inspected and compared. Our key findings include: 1) the essential role of anchors in label assignment; 2) the descriptive capability of the 2-point representation; 3) the crucial strategies for improving the detection of slender objects and regular objects. Our work identifies and extends the insights of existing methods that are previously underexploited. Furthermore, we propose a feature adaption strategy that achieves clear and consistent improvements over current representative object detection methods. In particular, a natural and effective extension of the center prior, which leads to a significant improvement on slender objects, is devised. We believe this work opens up new opportunities and calibrates ablation standards for future research in the field of object detection.