Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of the " Laying On of Hands" on Transplanted Breast Cancer in Mice

After witnessing numerous cases of cancer remission associated with a healer who used " laying on of hands" in New York, one of us (W.B. ) " apprenticed" in techniques alleged to reproduce the healing effect. We ob- tained five experimental mice with mammary adenocarcinoma (code: H2712; host strain: C3H/HeJ; strain of origin: C3H/HeHu ), which had a predicted 100% fatality between 14 and 27 days subsequent to injection. Bengston treated these mice for 1 hour per day for 1 month. The tumors developed a " blackened area," then they ulcerated, imploded, and closed, and the mice lived their normal life spans. Control mice sent to another city died within the predicted time frame. Three replications using skeptical volunteers (including D.K.) and laboratories at Queens College and St. Joseph' s College produced an overall cure rate of 87.9% in 33 experimental mice. An additional informal test by Krinsley at Arizona State resulted in the same patterns. Histological studies indicated viable cancer cells through all stages of remission. Reinjec- tions of cancer into the mice in remission in Arizona and New York did not take, suggesting a stimulated immunological response to the treatment. Our tentative conclusions: Belief in laying on of hands is not necessary in order to produce the effect; there is a stimulated immune response to treatment, which is reproducible and predictable; and the mice retain an immunity to the same cancer after remission. Future work should involve testing on various dis- eases and conventional immunological studies of treatment effects on experi- mental animals.
Musical instrument recognition using cepstral coefficients and temporal features

In this paper, a system for pitch independent musical instrument recognition is presented. A wide set of features covering both spectral and temporal properties of sounds was investigated, and their extraction algorithms were designed. The usefulness of the features was validated using test data that consisted of 1498 samples covering the full pitch ranges of 30 orchestral instruments from the string, brass and woodwind families, played with different techniques. The correct instrument family was recognized with 94% accuracy and individual instruments in 80% of cases. These results are compared to those reported in other work. Also, utilization of a hierarchical classification framework is considered.
$p$-adic L-functions of automorphic forms and exceptional zeros

Let F be a number field, p a prime number. We construct the (multi-variable) p-adic L-function of an automorphic representation of $GL_2(A_F)$ (with certain conditions at places above p and $\infty$), which interpolates the complex L-function at the central critical point. We use this construction to prove that the p-adic L-function of a modular elliptic curve E over F has vanishing order greater or equal to the number of primes above p at which E has split multiplicative reduction, as predicted by the exceptional zero conjecture. This is a generalization of analogous results by Spie{\ss} (arXiv:1207.2289) over totally real fields.
Old habits die hard: Why refactoring for understandability does not give immediate benefits

Depending on the context, the benefits of clean code with respect to understandability might be less obvious in the short term than is often claimed. In this study we evaluate whether a software system with legacy code in an industrial environment benefits from a “clean code” refactoring in terms of developer productivity. We observed both increases as well as decreases in understandability, showing that immediate increases in understandability are not always obvious. Our study suggests that refactoring code could result in a productivity penalty in the short term if the coding style becomes different from the style developers have grown attached to.
Female Veterans' Involvement in Outdoor Sports and Recreation

Abstract Previous research has recognized the need to better understand the experience of female veterans and their adjustment upon returning home, especially considering that a growing number of veterans are women. Their stories, particularly as they relate to combat and the associated wounds of war, largely remain untold. Therefore, the purpose of this project was to employ a theoretical sample from Grounded Theory methodology to determine if similar recreation opportunity structure patterns existed in the use of outdoor sports and recreation for a sample of female veterans, as had been found in previous research with individuals with physical disabilities. The investigation revealed findings that substantiated the way in which recreation opportunity structures provide novel environments where physical skills and emotional capacities could be developed through (a) establishing social networks and bonding, (b) facilitating a sense of freedom from constraints, and (c) by providing opportunities to redefine or recapture their identity.
End to End Learning for Self-Driving Cars

We trained a convolutional neural network (CNN) to map raw pixels from a single front-facing camera directly to steering commands. This end-to-end approach proved surprisingly powerful. With minimum training data from humans the system learns to drive in traffic on local roads with or without lane markings and on highways. It also operates in areas with unclear visual guidance such as in parking lots and on unpaved roads. The system automatically learns internal representations of the necessary processing steps such as detecting useful road features with only the human steering angle as the training signal. We never explicitly trained it to detect, for example, the outline of roads. Compared to explicit decomposition of the problem, such as lane marking detection, path planning, and control, our end-to-end system optimizes all processing steps simultaneously. We argue that this will eventually lead to better performance and smaller systems. Better performance will result because the internal components self-optimize to maximize overall system performance, instead of optimizing human-selected intermediate criteria, e.g., lane detection. Such criteria understandably are selected for ease of human interpretation which doesn't automatically guarantee maximum system performance. Smaller networks are possible because the system learns to solve the problem with the minimal number of processing steps. We used an NVIDIA DevBox and Torch 7 for training and an NVIDIA DRIVE(TM) PX self-driving car computer also running Torch 7 for determining where to drive. The system operates at 30 frames per second (FPS).
The Cost of Equity in Emerging Markets: A Downside Risk Approach

Every company evaluating an investment project or an acquisition in an emerging market must not only estimate future cash flows but also an appropriate discount rate. Although not free from controversy, the cost of equity in developed markets is typically estimated with the CAPM. In emerging markets, however, betas and stock returns seem to be unrelated. This article argues that total risk, idiosyncratic risk, and some measures of downside risk are significantly related to emerging-market stock returns, and proposes to estimate costs of equity in these markets based on the semideviation with respect to the mean, a well-known measure of downside risk.
Let Me See You! A Video Experiment on the Social Dimension of Risk Preferences

Previous studies have shown that decision makers are less other-regarding when their own payoff is risky than when it is sure. Empirical observations also indicate that people care more about identifiable than unidentifiable others. In this paper, we report on an experiment designed to explore whether rendering the other identifiable - via a short speechless video - can affect the relation between other-regarding concerns and attitudes toward social risk. For this sake, we elicit risk attitudes under two treatments differing in whether the actor can see the other or not. We find that seeing the other does not affect behavior significantly: regardless of the treatment, individuals are mainly self-oriented as to social allocation of risk, though they are other-regarding with respect to expected payoff levels.
Characteristics and Determinants of Intergenerational Financial Transfers Within Families Using Mixed Care for Elderly People

The provision of care to dependent elderly parents or parents-in- -law is an important part of intergenerational exchange within families, especially in countries where the long-term care system is based predominantly on family care. However, in mixed-care networks, care tasks are shared between family members and formal carers. Additionally, adult children may need to financially help their parents, especially due to the financial burden that formal care places on the elderly. We used the Slovenian national survey of social home care users and their family members, collected in 2013, to observe the characteristics and determinants of intergenerational financial transfers in families that use mixed care, within dyads comprising a care recipient and a family caregiver. The findings show that there is a considerable proportion of financial exchange among the observed dyads. Furthermore, among the determinants, the income of the elderly person and amount of care received are important for financial flows upward (to the elderly parent) and downward (from the elderly parent). The concurrent flows differ; their main determinants are the carer's age, household size and education.
Modification in „KNN‟ Clustering Algorithm for Distributed Data

- Clustering has become an increasingly important task in modern application domains such as marketing and purchasing assistance, multimedia, molecular biology etc. The goal of clustering is to decompose or partition a data set into groups such that both the intra-group similarity and the inter-group dissimilarity are maximized. In many applications, the size of the data that needs to be clustered is much more than what can be processed at a single site. Further, the data to be clustered could be inherently distributed. The increasing demand to scale up to these massive data sets which are inherently distributed over networks with limited bandwidth and computational resources has led to methods for parallel and distributed data clustering. In this thesis, we present a cohesive framework for cluster identification and outlier detection for distributed data. The core idea is to generate independent local models and combine the local models at a central server to obtain global clusters. A feedback loop is then provided from the central site to the local sites to complete and refine the global clusters obtained. Our experimental results show the efficiency and accuracy of our approach.
Uses of WhatsApp in the Spanish university student. Pros and cons

Introduction: The objective of this research was to analyse how the use of instant messaging services impacts the Spanish university context and what positive and negative consequences it generates on students’ behaviour. In order to do this, we worked on the most popular application in the territory in question, WhatsApp, and its use by university students. Methodology: The research developed has used the quantitative technique (survey to a sample n = 332) to determine the use that is given to conventional text messages, as well as other options for instant messaging (such as voice or images). Likewise, some impacts on the academic environment were analysed, such as the possible stress it generates on human behaviour. Results and conclusions: The main conclusions of the study include the convenience and free nature of WhatsApp that drive its use in the educational environment. It can be seen that the majority of students use this type of instant messaging applications also for issues related to university affairs -besides their personal lives. In addition, it has been found that a very high percentage of the groups analysed are members of a study-related chat group or is included in conversation groups on academic subjects.
Developmental Changes in the Effect of Inversion: Using a Picture Book to Investigate Face Recognition

A novel child-oriented procedure was used to examine the face-recognition abilities of children as young as 2 years. A recognition task was embedded in a picture book containing a story about two boys and a witch. The story and the task were designed to be entertaining for children of a wide age range. In eight trials, the children were asked to pick out one of the boys from amongst eight distractors as quickly as possible. Response-time data to both upright and inverted conditions were analysed. The results revealed that children aged 6 years onwards showed the classic inversion effect. By contrast, the youngest children, aged 2 to 4 years, were faster at recognising the target face in the inverted condition than in the upright condition. Several possible explanations for this ‘inverted inversion effect’ are discussed.
Unsupervised learning of an embodied representation for action selection

We propose a principle on how a computational agent can learn the structure of a classic discrete state space. The idea is to do a kind of principal component analysis on a matrix describing transitions from one state to another. This transforms the space of discrete, completely separate, states into a dimensional representation in a Euclidean space. The representation supports action selection, ideally turning action selection into a trivial problem: the route to a goal state can be directly obtained from the representation. Thus, the computations typically performed by dynamic programming and reinforcement learning are largely replaced by learning the representation. This has the benefit that the representation is not dependent on which state happens to be the goal state; thus, change of goal does not necessitate re-learning, which is in stark contrast to classic reinforcement learning theory.
Neonatal Learning of Faces : Environmental and Genetic Influences

Newborn face perception is controversial, but the current evidence suggests that (a) newborns follow face-like schematic patterns further than similar patterns, (b) infants can learn individual faces soon after birth, and (c) full face processing abilities develop through months or years of experience with faces. Previous models have not adequately accounted for all three types of results. In prior work, we showed how a biologically based self-organizing system and spontaneous activity patterns can explain newborn face preferences. In this paper we show that this general-purpose learning system can explain both neonatal and later learning. Using computational simulations, we demonstrate that newborn learning need not be based on the external outline, as has been supposed, and that postnatal decreases in response to schematic faces need not represent a decrease in response to real faces. These simulations provide concrete predictions to guide future experiments with infants, while suggesting new techniques for designing complex adaptive systems in general.
D3S: Debugging Deployed Distributed Systems

Testing large-scale distributed systems is a challenge, because some errors manifest themselves only after a distributed sequence of events that involves machine and network failures. D3S is a checker that allows developers to specify predicates on distributed properties of a deployed system, and that checks these predicates while the system is running. When D3S finds a problem it produces the sequence of state changes that led to the problem, allowing developers to quickly find the root cause. Developers write predicates in a simple and sequential programming style, while D3S checks these predicates in a distributed and parallel manner to allow checking to be scalable to large systems and fault tolerant. By using binary instrumentation, D3S works transparently with legacy systems and can change predicates to be checked at runtime. An evaluation with 5 deployed systems shows that D3S can detect non-trivial correctness and performance bugs at runtime and with low performance overhead (less than 8%).
Gender differences in applying for STEM programs in higher education: evidence from a policy shift in Hungary

We study how admission policies in higher education affect enrollment decisions of men and women and the decision to apply to STEM programs. More specifically, we investigate how an increase in the relative acceptance probability for STEM programs affects these decisions. We apply our analysis to Hungary and we evaluate a policy reform that limited access to subsidized non-STEM programs. We find that this change in the selectivity of the admission system differently affected application decisions of men and women. After the reform, fewer students applied to higher education and the reform especially discouraged the participation of women. After the reform, more men and women applied to STEM programs or non-subsidized non-STEM programs in which they have to pay tuition fees. This last effect is stronger for women. As the reform affected the chance to be admitted to higher education, we estimate a structural model to analyze how the responsiveness to admission probabilities in application decisions differs between men and women. We find that women are more sensitive to admission probabilities. Finally, we use the model to simulate the impact of alternative admission policies on enrollment in STEM programs. We find that an open access policy in STEM programs would stimulate more men and women to apply to these programs.
Students' perception of Online Assessment use in Schoology in EFL Classrooms

Nowadays, the use of technology has developed in the educational world. The students and lecturers could utilize or integrate technology in their teaching activities. One way to do it is by applying online assessment and this can be done with the assistance of technology. Schoology is one of the Learning Management System that can be used as a way to do online assessment. This study aims at identifying the students’ perception of the use of online assessment in Schoology; and examining the students’ challenges in doing online assessment. To answer these questions, the study employed a survey research to 120 students of English Teacher Education Department. The questionnaire consisted of both open and close-ended questions. The findings indicated that the students have positive perceptions toward the use of online assessment. There are the easiness in the use of Schoology because of the students' familiarity with the use of online technology, saving their time to do everywhere, and its goodness rather than paper assessment. However, there were also some students who had negative perceptions. They sometimes found that the Schoology is trouble and complicated. It may happen because they were not familiar with the online technology. Besides some perceptions stated above, there were several challenges that are faced by the students such as they must do the test fast and accurately because it is limited by time and the signal sometimes slow. However, the students felt happy doing the online assessment in Schoology because there was no controller for what they were doing in Schoology. In summary, the perceptions of students are not only positive but also negative with some challenges. They also expect that online assessment can be applied in other coursework for identifying the student progress.
Paraprofessional home visitation program to prevent childhood unintentional injuries in low-income communities: a cluster randomized controlled trial

Objective: To investigate the effectiveness of a paraprofessional home visitation program (HVP) to improve home safety and prevent injuries among children living in low-income settings. Methods: The HVP was implemented in two low-income communities in South Africa. In each community, approximately 200 households were randomly selected for the trial. Eligible households were those with children aged ⩽10 years. Intervention households received four visits, one every two weeks, by trained paraprofessionals that focused on a specific injury topic and consisted of: information dissemination about specific injury prevention practices; home inspection accompanied by information about home hazards; and the supply of safety devices. The key outcomes to measure the presence of home hazards were scores for burns (safety practices, paraffin, and electrical), poisoning, and falls. Results: Significant reductions were found for injury risks related to burn safety practices. For injury risks related to electrical burns, paraffin burns, and poisoning, a decline was also noted although this was not statistically significant. No decline was noted for fall-related risks. Conclusions: Subject to further replication and evaluation, home visits by paraprofessionals providing safety education, home inspection, and safety devices be considered for integration into a comprehensive child injury prevention strategy in low-income communities.
Influence of Preoperative Chemotherapy on the Risk of Major Hepatectomy for Colorectal Liver Metastases

Objective:To assess the effects of preoperative systemic chemotherapy on remnant liver parenchyma, liver function, and morbidity after major liver resection for colorectal liver metastases. Background:Many patients operated upon for colorectal cancer liver metastases receive previous chemotherapy. Whether systemic chemotherapy alters liver parenchyma in such way that it increases the risks of liver resection remains unclear. Patients and Methods:Among 214 patients who received a liver resection for colorectal liver metastases between 1998 and 2002 in a single institution, 67 who underwent a major liver resection under total hepatic vascular exclusion form the basis of this report. Forty-five patients operated upon after systemic chemotherapy were compared with 22 who did not receive any chemotherapy in the 6 months prior to resection. Postoperative mortality, morbidity, liver function tests, and pathology of the resected liver in the two groups were compared. Results:There was no postoperative mortality. Values of liver function tests on days 1, 3, 5, and 10 were similar in both groups. Morbidity rate was higher in the chemotherapy group (38% versus 13.5%, P = 0.03). Postoperative morbidity was correlated with the number of cycles of chemotherapy administered before surgery but not to the type of chemotherapy. Preoperative chemotherapy was significantly associated with sinusoidal dilatation, atrophy of hepatocytes, and/or hepatocytic necrosis (49% versus 25%, P = 0.005). Conclusion:Prolonged neoadjuvant systemic chemotherapy alters liver parenchyma and increases morbidity after major resection under total hepatic vascular exclusion, but it does not increase operative mortality. This should be taken into consideration before deciding a major liver resection in patients who have received preoperative chemotherapy.
3D TREETOP POSITIONING BY MULTIPLE IMAGE MATCHING OF AERIAL IMAGES IN A 3D SEARCH VOLUME BOUNDED BY LIDAR SURFACE MODELS

This paper presents a method for semi-automatic 3D positioning of tree tops that can be used for obtaining tree maps of the photovisible trees and tree heights. Such spatio-temporal, detailed information is usable for many applications in e.g. forestry and landscape management. The method incorporates the use of passive, high-resolution optical images with co-existent low-resolution airborne lidar data. The latter is used for confining the search space of image matching to agree with the volume of photo-visible trees in the upper canopy and for obtaining an accurate elevation model, which is paramount for reliable tree height estimation. The method is presented here and tested with restricted image and field material.