Miracle-dz/UniFAR-FTUs huggingface dataset:
Rage Against the Machines: Labor-Saving Technology and Unrest in Industrializing England

Can new technology cause social instability and unrest? We examine the famous “Captain Swing” riots in 1830s England. Newly collected data on threshing machine diffusion shows that labor-saving technology was associated with more riots. We instrument technology adoption with the share of heavy soils in a parish: IV estimates demonstrate that threshing machines were an important cause of unrest. Where alternative employment opportunities softened the blow of new technology, there was less rioting. Conversely, where enclosures had impoverished workers, the effect of threshing machines on rioting was amplified. (JEL J24, L16, N13, N33, N53, O33, Q16)
Functional role of the nicotinic arm of the acetylcholine regulatory axis in human B-cell lines

We studied the involvement of nicotinic acetylcholine receptors (nAChRs) in the inflammation-related activity of human B-cell lines. Activation of nAChRs in Daudi cells with epibatidine abolished the pansorbin-dependent upregulation of the pro-inflammatory marker Cox-2 both at the mRNA and protein levels, indicating that the nicotinergic signaling suppresses B-cell activation. While the anti-inflammatory action on B-cells was mediated predominantly through α7 nAChR, as could be judged from abolishing epibatidine effects with methyllycaconitine, both α7 and non-α7 nAChRs, such as α2-containing receptors, were involved in regulation of B-cell apoptosis. The net effect was antiapoptotic. To determine the role of nAChRs in regulating B-cell activation/plasmacytic differentiation, we measured changes in the CD38, CD138 and Bcl-6 gene expression. Epibatidine significantly (P < 0.05) upregulated CD38 at the transcriptional level and CD138 and Bcl-6 – at the translational levels. AR-R17779 significantly (P < 0.05) increased the protein levels of CD38 and CD138. In both cases, the effect of epibatidine was abolished with Mec, and that of AR-R17779 – by MLA, demonstrating a functional role of nAChRs in regulating Daudi cell differentiation. The obtained results revealed distinct contributions of α7 and non-α7 nAChRs to regulation of B-cell activation/differentiation, and suggested that signaling through the nicotinic arm of acetylcholine regulatory axis is important for B-cell involvement in inflammation.
Group decision‐making based on pythagorean fuzzy TOPSIS method

Group decision‐making is a process wherein multiple individuals interact simultaneously, analyze problems, evaluate the possible available alternatives, characterized by multiple conflicting criteria, and choose suitable alternative solution to the problem. Technique for establishing order preference by similarity to the ideal solution (TOPSIS) is a well‐known method for multiple‐criteria decision‐making. The purpose of this study is to extend the TOPSIS method to solve multicriteria group decision‐making problems equipped with Pythagorean fuzzy data, in which the assessment information on feasible alternatives, provided by the experts, is presented as Pythagorean fuzzy decision matrices having each entry characterized by Pythagorean fuzzy numbers. A revised closeness index is utilized to obtain the ranking of alternatives and to identify the optimal alternative. The developed Pythagorean fuzzy TOPSIS (PF‐TOPSIS) is illustrated by a flow chart. At length, practical examples interpreting the applicability of our proposed PF‐TOPSIS are solved.
Understanding Backdoor Attacks through the Adaptability Hypothesis

A poisoning backdoor attack is a rising security concern for deep learning. This type of attack can result in the backdoored model functioning normally most of the time but exhibiting abnormal behavior when presented with inputs containing the backdoor trigger, making it difficult to detect and prevent. In this work, we propose the adapt-ability hypothesis to understand when and why a backdoor attack works for general learning models, including deep neural networks, based on the theoretical investigation of classical kernel-based learning models. The adaptability hypothesis postulates that for an effective attack, the effect of incorporating a new dataset on the predictions of the original data points will be small, provided that the original data points are distant from the new dataset. Experiments on benchmark image datasets and state-of-the-art backdoor attacks for deep neural networks are conducted to corroborate the hypothesis. Our finding provides insight into the factors that affect the attack’s effectiveness and has implications for the design of future attacks and defenses.
Growth and Physiological Performance in Growth Phenotypes of the Carpet Shell Clam (Ruditapes decussatus) Fed Diets of Variable Lipid/Carbohydrate Ratios

Mixed suspensions of phytoplankton and yeast cells in different proportions were designed to achieve diets with a range of variation (0.6–2.2) in the ratio of lipid to carbohydrate while maintaining protein content constant. Juvenile specimens of the carpet shell clam (Ruditapes decussatus) from two segregated growth phenotypes (fast and slow growers) were food conditioned and the physiological components of the energy balance were determined with these different diet compositions in order to assess the combined effects of endogenous and nutritional factors on growth performance. Conditioning to lipid-rich diets increased growth rate relative to conditioning to carbohydrate-rich diets and resulted in higher scope for growth values in both growth groups. These dietary effects are mainly driven by differences in the absorption efficiency (AE) found between clams fed different food compositions, although the present results do not allow to ascertain whether the reduced AE recorded with the carbohydrate-rich diets results from reduced digestibility of yeasts cells due to structural restrictions or either reflects the digestive imbalance of lipids associated to higher production of metabolic fecal losses. Greater phenotypic plasticity was seen to enable the fast-growing clams fed a carbohydrate-rich diet to overcome the above digestive limitations through an overfeeding response; however, the resource to such kind of physiological mechanism appeared limited by the nutritional conditions (energetic status) prevailing during the conditioning phase.
Approximating probabilistic explanations via supermodular minimization

Explaining in accurate and intelligible terms the predictions made by classifiers is a key challenge of eXplainable Artificial Intelligence (XAI). To this end, an abductive explanation for the predicted label of some data instance is a subset-minimal collection of features such that the restriction of the instance to these features is sufficient to determine the prediction. However, due to cognitive limitations, abductive explanations are often too large to be interpretable. In those cases, we need to reduce the size of abductive explanations, while still determining the predicted label with high probability. In this paper, we show that finding such probabilistic explanations is NP-hard, even for decision trees. In order to circumvent this issue, we investigate the approximability of probabilistic explanations through the lens of supermodularity. We examine both greedy descent and greedy ascent approaches for supermodular minimization, whose approximation guarantees depend on the curvature of the “unnormalized” error function that evaluates the precision of the explanation. Based on various experiments for explaining decision tree predictions, we show that our greedy algorithms provide an efficient alternative to the state-of-the-art constraint optimization method.
Bayesian Clustering by Dynamics Marco Ramoni

This paper introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to discover the most probable set of clusters capturing different dynamics. To increase ef£ciency, the method uses an entropy-based heuristic search strategy. A controlled experiment suggests that the method is very accurate when applied to arti£cial time series in a broad range of conditions and, when applied to clustering sensor data from mobile robots, it produces clusters that are meaningful in the domain of application.
THE QUARTERLY JOURNAL OF ECONOMICS

Classroom education has public good aspects. The technology is such that when one student disrupts the class, learning is reduced for all other students. A disruption model of educational production is presented. It is shown that optimal class size is larger for better-behaved students, which helps explain why it is difﬁcult to ﬁnd class size effects in the data. Additionally, the role of discipline is analyzed and applied to differences in performance of Catholic and public schools. An empirical framework is discussed where the importance of sorting students, teacher quality
Validation of evaluating instrument for training nurses in cardiopulmonary resuscitation / Validação de instrumento avaliativo para capacitação de enfermeiros em ressuscitação cardiopulmonar

Objetivo: validar critérios de um instrumento para avaliação da capacitação de enfermeiros em ressuscitação cardiopulmonar. Método: estudo metodológico para validação de critério de um instrumento previamente validado quanto ao conteúdo. Realizou-se a aplicação de um instrumento pré e pós-teste de uma capacitação com 20 enfermeiros de um hospital do interior do Estado de São Paulo. Resultados: realizou-se a análise das respostas do pré e pós-teste sobre o entendimento dos participantes antes e após a realização de teoria atrelada a simulação sobre ressuscitação cardiopulmonar. Foram avaliadas as variáveis objetividade, simplicidade, clareza e pertinência, destacando-se que os participantes concordaram que os critérios citados foram atendidos. Conclusão: o instrumento investigado possui relação com os padrões definidos, sendo comprovadamente validado. Ao utilizar-se deste instrumento durante a avaliação de capacitações em ressuscitação cardiopulmonar, as equipes de trabalho, alunos e pacientes serão beneficiados, garantindo a padronização e melhor efetividade no atendimento a PCR.
Monitoring Snow Cover and Modelling Catchment Discharge With Remote Sensing in the Upper Waitaki Basin, New Zealand

Because New Zealand relies heavily on water for electricity generation, it requires strong and reliable information about its water supplies as well as better knowledge about the processes that affect them. Situated in the Southern Alps, the Waitaki basin is the most important hydro catchment in New Zealand. Three alpine sub-catchments, namely Ohau, Pukaki, and Tekapo, provide most of the discharge to the Waitaki River. In this alpine region a large part of the water resource is temporarily stored as seasonal snow cover. To utilize better the value of water in hydro lakes, improving knowledge of the timing and supply of water from seasonal snow is a priority. It has been long established that satellite remote sensing is a powerful tool to monitor snow cover in remote and inaccessible areas. In New Zealand, this technology has received only scant consideration. In addressing the remote sensing of the seasonal snow cover in the alpine catchments of the Waitaki basin, this thesis aims at filling a considerable void. This is achieved through the implementation of routine monitoring of the snow cover dynamics with the MODerate Imaging Spectro-radiometer (MODIS). Towards this goal, several advanced remote sensing techniques that are novel to MODIS are integrated in a single and operational algorithm. This research demonstrates the desirable performance of an image fusion algorithm. The algorithm enables the mapping of snow with MODIS at 250m spatial resolution instead of the 500m spatial resolution imagery currently available. Furthermore, MODIS images are standardized by means of a physically-based atmospheric and topographic correction (ATOPCOR) approach. Finally, the radiometric normalization of the time series permits the design of a robust spectral unmixing technique. This allows further enhancement of the spatial details of the snow maps through the determination of sub-pixel snow fractions at 250m spatial resolution. Together, the combination of these techniques forms a processing chain, well suited
ZEF-Discussion Papers on Development Policy No. 186

Do transgenic crops cause agrobiodiversity erosion? We hypothesize that they increase productivity and reduce production risk and may therefore reduce farmer demand for onfarm varietal diversity, especially when only a few transgenic varieties are available. We also hypothesize that varietal diversity can be preserved when more transgenic varieties are supplied. These hypotheses are tested and confirmed with panel data for the case of transgenic cotton in India. Cotton varietal diversity in India, with of over 90% adoption of transgenic technology, is now at the same level than it was before the introduction of this technology. Some policy implications are discussed.
Reflections on the Inter-Industry Wage Structure

This paper reviews available evidence on the inter-industry wage structure. The inter-industry wage structure is remarkably similar in different eras, in different countries, and among different types of workers. Industries with high capital-to-labor ratios, monopoly power and high profits pay relatively high wages. We conclude that the competitive model cannot without substantial modification provide an adequate explanation of the inter-industry wage structure. The implications of this finding for micro and macro economic theory and policy are examined.
Ethnotaxonomical Approach in the Identification of Useful Medicinal Flora of Tehsil Pindigheb (District Attock) Pakistan

The presented research investigated the use of folk remedies among the people of Tehsil Pindigheb, District Attock of Pakistan. During the ethnobotanical survey, we documented indigenous knowledge and collected plant specimens which included medicinal plants. Through questionnaire, ethnomedicinal data was collected from key informants and local inhabitants in randomly selected villages. One hundred plant species belonging to 44 families were recorded as medicinal flora of the area. Due to construction of new housing colonies, modern agricultural practices and cultural changes within the community, the use of traditional knowledge and medicinal plant species are threatened day by day in the area. This study will provide help in future conservation strategies.
UvA-DARE ( Digital Academic Repository ) Bayesian inference for psychology . Part II

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of userfriendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (www.jasp-stats.org), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses Eric-Jan Wagenmakers EJ.Wagenmakers@gmail.com 1 Department of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ Amsterdam, The Netherlands 2 Birla Institute of Technology and Science, Pilani, India 3 Masaryk University, Brno, Czech Republic 4 University of California at Irvine, Irvine, CA, USA 5 University of Missouri, Columbia, MO, USA 6 Cardiff University, Cardiff, UK implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.
The Effect of Altered Mucin1, FGF2, and HBEGF Gene Expression at The Ectopic Implantation Site and Endometrial Tissues in The Tubal Pregnancy Pathogenesis: A Case-Control Study

Background: Ectopic pregnancy (EP) is defined as implantation and development of an embryo outside of the uterine tissue. Women undergoing assisted reproductive technologies (ART), particularly frozen embryo transfer (FET), are in high-risk populations for EP. Mucin1 (MUC1), fibroblast growth factor-2 (FGF2), and Heparin-binding epidermal growth factor (HBEGF) genes are involved in the endometrial receptivity pathway, leading to normal eutopic implantation; Although, their relevance in the tubal pregnancy after FET is unknown. We aimed evaluation of Mucin1, FGF2, and HBEGF expression fold as endometrial receptive markers in the EP patients following the FET cycle. Materials and Methods: A case-control study was conducted on ten patients (five EP patients and five women in the pseudo-pregnancy group, as the control samples). Pseudo-pregnancy group was established in women who were candidates for hysterectomy for benign diseases. Fallopian tube biopsies and corresponding endometrial tissues from these patients were taken during the hysterectomy. However, the fallopian tube and endometrial tissues of EP patients were obtained during salpingectomy. The mRNA expressions of MUC1, FGF2, and HBEGF genes in the fallopian tube and endometrial tissues were measured by real-time polymerase chain reaction (PCR) assay. Results: MUC1 mRNA expression level in the endometrium of the case group was higher than in the control group (P=0.04); however, its mRNA expression in the fallopian samples of the case group in comparison with the control group was significantly decreased (P=0.001). The HBEGF mRNA expression level was not significantly different between the case and control endometrium, whereas its expression was significantly increased in the case fallopian samples compared with the control ones (P=0.001). The same pattern was observed for FGF2 mRNA expression level in the fallopian samples of the case group but was significantly reduced in the endometrial samples in comparison with the control samples (P=0.03). Conclusion: MUC1, FGF2, and HBEGF gene mRNA expression changes may explain the embryo rejection from the uterus and the establishment of a receptive phenotype in fallopian cells.
Ageing: the social and demographic dimensions

As fertility and mortality rates fall, populations age. In Australia, as in other advanced industrialised countries, fertility and mortality rates have been falling for more than a century. In 1870, 42 per cent of Australia’s population was aged less than 15 years and 2 per cent was aged 65 years and over. In 1998, 21 per cent was aged less than 15 years and 12 per cent was aged 65 years and over. Thus, ageing is not a new phenomenon. Being an outcome of increased control over both fertility and mortality, ageing for the last century has generally been welcomed, so why is it that ageing has now become a major issue? The suddenness of the emergence of ageing as an issue is indicated by the lack of concern expressed about ageing in the 1975 Report of the National Population Inquiry (the Borrie Report). Indeed, the ageing of the population received only passing mention in this, the most comprehensive report on Australia’s population ever undertaken and no mention at all in the concluding chapters related to policy.
Benign Overfitting in Two-layer ReLU Convolutional Neural Networks

Modern deep learning models with great expressive power can be trained to overfit the training data but still generalize well. This phenomenon is referred to as \textit{benign overfitting}. Recently, a few studies have attempted to theoretically understand benign overfitting in neural networks. However, these works are either limited to neural networks with smooth activation functions or to the neural tangent kernel regime. How and when benign overfitting can occur in ReLU neural networks remains an open problem. In this work, we seek to answer this question by establishing algorithm-dependent risk bounds for learning two-layer ReLU convolutional neural networks with label-flipping noise. We show that, under mild conditions, the neural network trained by gradient descent can achieve near-zero training loss and Bayes optimal test risk. Our result also reveals a sharp transition between benign and harmful overfitting under different conditions on data distribution in terms of test risk. Experiments on synthetic data back up our theory.
Linguistic Typology

This article looks at cross-linguistic variation in lexical iconicity, addressing the question of to what extent and how this variation is patterned. More than in spoken languages, iconicity is highly frequent in the lexicons of sign languages. It is also highly complex, in that often multiple motivated components jointly shape an iconic lexeme. Recent typological research on spoken languages finds tentative iconic patterning in a large number of basic lexical items, underlining once again the significance of iconicity for human language. The uncontested and widespread use of iconicity found in the lexicons of sign languages enables us to take typological research into lexical iconicity to the next level. Indeed, previous studies have shown cross-linguistic variation in: a) the use of embodying and handling handshapes in sign languages (mostly of European origin) and b) the frequency of space-based size depiction in African and European sign languages. The two types of variation may be interrelated, as handling handshapes may use space-based size depiction. In this study, we first replicate earlier studies on the distribution of embodying and handling handshapes, this time in a data set consisting of a relatively large set of sign languages (n = 11), most of which are used in Africa. The results confirm significant variation across these sign languages. These findings are then compared to the use of space-based size depiction, revealing that these patterns independently from the distribution of embodying/handling handshapes. We argue that the results call for expanding typological studies on representational strategies in iconic signs beyond the now relatively well studied instrument/manipulation alternation. Fine-grained analyses on a multitude of iconic features in signs are likely to reveal cross-linguistic variation in iconic tendencies in SL lexicons.
Supplementary Material for “3D Line Mapping Revisited”

Full Acknowledgements. We sincerely thank the reviewers for their constructive feedback. We are grateful to Philipp Lindenberger, Paul-Edouard Sarlin, Johannes Schönberger for their open-source projects, Iago Suárez, Hengkai Guo, Daniel Barath, Siyan Dong, Martin Oswald, Jing Ren, Iro Armeni for helpful discussions, Marcel Geppert, Daniel Thul, Peizhuo Li for technical support on Blender. Special thanks to Mihai Dusmanu and Wang Zhao for proof-reading. Viktor Larsson received funding by the strategic research project ELLIIT.
Optimizing Well-Being: The Empirical Encounter of Two Traditions

Subjective well-being (SWB) is evaluation of life in terms of satisfaction and balance between positive and negative affect; psychological well-being (PWB) entails perception of engagement with existential challenges of life. The authors hypothesized that these research streams are conceptually related but empirically distinct and that combinations of them relate differentially to sociodemographics and personality. Data are from a national sample of 3,032 Americans aged 25–74. Factor analyses confirmed the related-but-distinct status of SWB and PWB. The probability of optimal well-being (high SWB and PWB) increased as age, education, extraversion, and conscientiousness increased and as neuroticism decreased. Compared with adults with higher SWB than PWB, adults with higher PWB than SWB were younger, had more education, and showed more openness to experience.