Miracle-dz/UniFAR-FTUs huggingface dataset:
Serie Documentos de Trabajo del IIEP

RESUMEN AN APPLICATION OF SEARLE’S THEORY OF SOCIAL PHENOMENA TO NEW INSTITUTIONAL ECONOMICS Javier Legris UNIvERSIDAD DE BUENOS AIRES. FACULTAD DE CIENCIAS ECONóMICAS. DEPARTAMENTO DE HUMANIDADES. BUENOS AIRES, ARgENTINA. CONICET-UNIvERSIDAD DE BUENOS AIRES. INSTITUTO INTERDISCIPLINARIO DE ECONOMíA POLíTICA DE BUENOS AIRES (IIEP-BAIRES). BUENOS AIRES, ARgENTINA. CONSEJO NACIONAL DE INvESTIgACIONES CIENTíFICAS Y TéCNICAS -UNIvERSIDAD DE BUENOS AIRES. INSTITUTO INTERDISCIPLINARIO DE ECONOMíA POLíTICA DE BUENOS AIRES (IIEP-BAIRES). BUENOS AIRES, ARgENTINA. In Economics the notion of institution is not sufficiently defined, at least not in a formal way. In this paper, some elements of Searle’s foundation for the formal study of social phenomena are taken to propose a more comprehensive and formal characterization of the concept. Also, for the purposes of an intuitive understanding of the proposal’s attributes, it is tried out an application to the concept of institution in the case of New Institutional Economics, at least Williamson’s account (1975). En economía, la noción de institución no está claramente definida, al menos no de manera formal. En este documento, se toman algunos elementos de los fundamentos de Searle para el estudio formal de los fenómenos sociales con el objetivo de proponer una caracterización más completa y formal del concepto. Además, a los efectos de una comprensión intuitiva de la propuesta, se ha ensayado una aplicación del concepto de institución en el caso de la aproximación Williamson (1975) a la New Institutional Economics.
Towards Optimal Separations between Quantum and Randomized Query Complexities

The query model offers a concrete setting where quantum algorithms are provably superior to randomized algorithms. Beautiful results by Bernstein-Vazirani, Simon, Aaronson, and others presented partial Boolean functions that can be computed by quantum algorithms making much fewer queries compared to their randomized analogs. To date, separations of $O(1)$ vs. $\sqrt{N}$ between quantum and randomized query complexities remain the state-of-the-art (where $N$ is the input length), leaving open the question of whether $O(1)$ vs. $N^{1/2+\Omega(1)}$ separations are possible? We answer this question in the affirmative. Our separating problem is a variant of the Aaronson-Ambainis k-fold Forrelation problem. We show that our variant: 1)Can be solved by a quantum algorithm making $2^{O(k)}$ queries to the inputs. 2)Requires at least $\widetilde{\Omega}(N^{2(k-1)/(3k-1)})$ queries for any randomized algorithm. For any constant $\epsilon > 0$, this gives a $O(1)$ vs. $N^{1/2-\epsilon}$ separation between the quantum and randomized query complexities of partial Boolean functions. Our proof is Fourier analytical and uses new bounds on the Fourier spectrum of classical decision trees, which could be of independent interest. Looking forward, we conjecture that the Fourier bounds could be further improved in a precise manner, and show that such conjectured bounds imply optimal $O(1)$ vs. $N^{1-\epsilon}$ separations between the quantum and randomized query complexities of partial Boolean functions.
On the Power of Randomization for Scheduling Real-Time Traffic in Wireless Networks

In this paper, we consider the problem of scheduling real-time traffic in wireless networks under a conflict-graph interference model and single-hop traffic. The objective is to guarantee that at least a certain fraction of packets of each link are delivered within their deadlines, which is referred to as delivery ratio. This problem has been studied before under restrictive frame-based traffic models, or greedy maximal scheduling schemes like LDF (Largest-Deficit First) that can lead to poor delivery ratio for general traffic patterns. In this paper, we pursue a different approach through randomization over the choice of maximal links that can transmit at each time. We design randomized policies in collocated networks, multipartite networks, and general networks, that can achieve delivery ratios much higher than what is achievable by LDF. Further, our results apply to traffic (arrival and deadline) processes that evolve as positive recurrent Markov chains. Hence, this work is an improvement with respect to both efficiency and traffic assumptions compared to the past work. We further present extensive simulation results over various traffic patterns and interference graphs to illustrate the gains of our randomized policies over LDF variants.
Broadcasting of H.264/SVC video over BitTorrent-like networks

BitTorrent protocol-based networks are the most popular peer-to-peer (P2P) configurations for data sharing in the Internet. One of the keys for its success is the prioritization of the less popular parts of the files so peers send first those chunks owned by the smallest amount of clients. The same algorithm that maximizes the bit-rate also prevents the lowdelay transmission of multimedia contents because data streams are not sequentially sent. An alternative approach -still compatible with the standard BitTorrent protocolwould be the application of the same selection policy but applied to a sliding window which is moved from the beginning to the end of the stream. Unfortunately, this solution imposes to peers severe temporal restrictions for retrieving data from the rest of peers, causing significant variations of the downstream bit-rate. The developed proposal addresses this drawback transmitting scalable video streams instead of non-scalable streams. In order to determine the efficiency of our approach, a set of experiments have been carried out. Results reveal that a SVC-based (Scalable Video Coding) approach outperforms the standard non scalable (AVC) under certain circunstances. Specifically, when high encoding bit-rates are selected and streams are truncated by a drop of the transmission bit-rate.
Atf6alpha impacts cell number by influencing survival, death and proliferation

Background: A growing body of literature suggests the celleintrinsic activity of Atf6a during ER stress responses has implications for tissue cell number during growth and development, as well as in adult biology and tumorigenesis [1]. This concept is important, linking the cellular processes of secretory protein synthesis and endoplasmic reticulum stress response with functional tissue capacity and organ size. However, the field contains conflicting observations, especially notable in secretory cell types like the pancreatic beta cell. Scope of review: Here we summarize current knowledge of the basic biology of Atf6a, along with the pleiotropic roles Atf6a plays in cell life and death decisions and possible explanations for conflicting observations. We include studies investigating the roles of Atf6a in cell survival, death and proliferation using well-controlled methodology and specific validated outcome measures, with a focus on endocrine and metabolic tissues when information was available. Major conclusions: The net outcome of Atf6a on cell survival and cell death depends on cell type and growth conditions, the presence and degree of ER stress, and the duration and intensity of Atf6a activation. It is unquestioned that Atf6a activity influences the cell fate decision between survival and death, although opposite directions of this outcome are reported in different contexts. Atf6a can also trigger cell cycle activity to expand tissue cell number through proliferation. Much work remains to be done to clarify the many gaps in understanding in this important emerging field. 2019 Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Bulletin of the Geological Society of Greece

The Ecological Footprint (EF) measures how much of the biosphere’s annual regenerative capacity is required to renew the natural resources used by a defined population in a given year. In essence, the EF is a resource accounting tool that measures how much biologically productive land and sea is used by a given population or activity, and compares this with the available land and sea. Productive land and sea support population demands for food, fiber, timber, energy, and space for infrastructure. These areas also absorb gaseous emissions (i.e. CO2) generated from human activities. The present paper discusses a methodology that allows the parametric estimation of the EF due to the transport of aggregates to urban areas as a function of tonnage and distance.
Design and Implementation OF probabilistic assignment Investment Management System. Using OOP

Computerized information system has recently become widely available. indeed ,it has become an important instrument that can be applied in different aspects of life . one of the important applications of computer systems is that adopted by commercial establishments as well as by small business . that ,we may admit that no management can successfully operate in any business without the use of computerized information system. One of the important applications of computer is to use it in the management of establishments such as companies and banks. There are many different systems that are used to manage investment; these systems use different design philosophy such as top down approach or modular approach. In this paper, the object oriented programming concept is applied to design and implement probabilistic assignment investment management system for commercial bank. Most applications of OOP use specialized object oriented languages, but this paper shows that C++ can be used effectively to developed object oriented models of typical investment management ,and implement OOP is more flexible and reliable and least costing.
University of Birmingham A bilingual advantage? An appeal for a change in perspective and recommendations for future research

: The debate on possible cognitive advantages bilinguals have over monolinguals continues to occupy the research community. There is an ever-growing research body focusing on adjudicating whether there is, in fact, an e ﬀ ect of using two or more languages regularly on cognition. In this paper, we brieﬂy review some of the more pertinent literature that has attempted to identify attenuating, modulating, and confounding factors in research comparing monolingual and bilingual populations, and we highlight issues that should be taken into account in future research to move forward as a research community. At the same time, we argue for a change in perspective concerning what is deemed an advantage and what is not and argue for more ecologically valid research that investigates real-life advantages.
Joint Triangulation and Mapping via Differentiable Sensor Fusion

The challenge of sensor fusion is prevalent in route planning, robotics, and autonomous vehicles. We leverage automatic differentiation (AD) and probabilistic programming to develop an end-to-end stochastic optimization algorithm for sensor fusion and triangulation of a large number of unknown objects. Our algorithm uses a generative model to train a Expectation Maximization (EM) clustering solver. We validate our method on street sign detections extracted from noisily geo-located street level imagery without depth information by jointly estimating the number and location of objects of different types, together with parameters for sensor noise characteristics and prior distribution of objects. We find that our model is more robust to upstream misclassifications than current methods and generalizes across sign types.
Hup-Type Hydrogenases of Purple Bacteria: Homology Modeling and Computational Assessment of Biotechnological Potential

Three-dimensional structures of six closely related hydrogenases from purple bacteria were modeled by combining the template-based and ab initio modeling approach. The results led to the conclusion that there should be a 4Fe3S cluster in the structure of these enzymes. Thus, these hydrogenases could draw interest for exploring their oxygen tolerance and practical applicability in hydrogen fuel cells. Analysis of the 4Fe3S cluster’s microenvironment showed intragroup heterogeneity. A possible function of the C-terminal part of the small subunit in membrane binding is discussed. Comparison of the built models with existing hydrogenases of the same subgroup (membrane-bound oxygen-tolerant hydrogenases) was carried out. Analysis of intramolecular interactions in the large subunits showed statistically reliable differences in the number of hydrophobic interactions and ionic interactions. Molecular tunnels were mapped in the models and compared with structures from the PDB. Protein–protein docking showed that these enzymes could exchange electrons in an oligomeric state, which is important for oxygen-tolerant hydrogenases. Molecular docking with model electrode compounds showed mostly the same results as with hydrogenases from E. coli, H. marinus, R. eutropha, and S. enterica; some interesting results were shown in case of HupSL from Rba. sphaeroides and Rvi. gelatinosus.
Artificial Intelligence for Games ( 2019 ) Prof . Dr . Köthe Training robots with machine learning : Juggling & Throwing

This report looks at the paper “Robot Juggling: An Implementation of Memory-based Learning” by Stefan Schaal and Christopher G. Atkeson [1], released 1994, describing their realization of a robot learning the task of juggling via machine learning. Basic concepts and techniques used in the paper will be introduced. At the end there will be also be a short summary of the more recent paper “TossingBot: Learning to Throw Arbitrary Objects with Residual Physics” by A. Zeng, S. Song, J. Lee, A. Rodriguez, and T. Funkhouser [2], in which they show how a robot arm can learn to throw objects by combining physical models and machine learning.
An Analysis of Superintendent and Principal Perceptions Regarding the Supervision and Evaluation of Principals

The goals for this study were to examine principals’ perceptions regarding their own supervision and evaluation and compare to superintendents’ perceptions regarding the supervision and evaluation of principals. Three research questions guided the inquiry: (1) What are the perceptions of principal and superintendents’ regarding their own supervision? ; (2) What are the perceptions of principal and superintendents’ regarding their own evaluation? ; and (3) What are the differences in perceptions of principal and superintendents’ regarding supervision and evaluation? This study followed a descriptive format and used a 20 item on-line survey to measure principal and superintendents’ perceptions regarding critical elements in their own supervision and evaluation cycle. Out of the participants solicited, 102 principals agreed to participate (37% response rate) and 23 superintendents agreed to participate (48% response rate). Results indicated overall superintendents and principals were in agreement regarding 19 out of 20 statements describing the supervision and evaluation of principals. In addition, there was a significant difference in both supervision and evaluation perceptions between superintendents and principals. Results from this study provide implications for those who supervise principals, as well as for those who train superintendents.
An Improved, Negatively Correlated Search for Solving the Unit Commitment Problem’s Integration with Electric Vehicles

With the rapid development of plug-in electric vehicles (PEVs), the charging of a number of PEVs has already brought huge impact and burden to the power grid, particularly at the medium and low voltage distribution networks. This presents a big challenge for further mass roll-out of electric vehicles. To assess the impact of charging of substantial number of electric vehicles on the grid, a model of 30000 PEVs integrated with unit commitment (UCEV) was investigated in this study. The unit commitment was a large-scale, mixed-integer, nonlinear, NP-Hard (non-deterministic polynomial) optimization problem, while the integration of PEVs further increased the complexity of the model. In this paper, a global best inspired negatively correlated search (GBNCS) method which extends the evolutionary logic of negatively correlated search is proposed to tackle the UCEV problem. In the proposed algorithm, a rounding transfer function in GBNCS, is deployed to convert real-valued variables into binary ones; further, the global best information is combined in the population to improve the efficiency of the algorithm. Numerical results confirmed that the proposed GBNCS can achieve good performance in both a basic IEEE 10 unit commitment problem and the UCEV problem. It was also shown that, among four charging modes, the off-peak charging mode and EPRI (Electric Power Research Institute) charging mode are more economical in PEV charging.
University of Birmingham Models and approaches to family-focused policy and practice

A review of models and approaches to family-based policy and service provision for those at risk of social exclusion suggests three distinct categories. In the ﬁrst category, approaches seek to strengthen the ability of family members to offer support to a primary service user within that family. In the second category, family members are recognised as having their own speciﬁc and independent needs arising out of their relationship with the primary service user. The third category includes ‘whole family approaches’ focused on shared needs and strengths that could not be dealt with through a focus on family members as individuals
Advanced Feature Extraction of Long-Term Epileptic Electroencephalography Records

Recent advances in artificial intelligence (AI) offer many opportunities to implement it in a broad range of industries. One of the main ambitious application of AI is in healthcare and patient monitoring. In healthcare industry, unlike the most commercial applications of AI, a missed detection/prediction of a clinical event may result in the death of a patient. Moreover, a high false alarm rate may lead to misdiagnosis causing extra effort and cost for care providers. Thus, in healthcare applications, it is required to strictly minimize the number of false alarms without sacrificing the sensitivity rate of the detection system. This dissertation focuses on epileptic seizure detection and classification in long-term electroencephalogram (EEG) records. More specifically, the two main challenges in supervised EEG seizure detection, the curse of dimensionality and the curse of variability are tackled. First, a signal decomposition technique, applicable to physiological signals, is devised which can be used as a preliminary step for feature extraction. This is performed by proposing a novel time-frequency transform based on rational functions, namely, rational short time Fourier transform (RSTFT). A sparse decomposition method is then proposed by reconstructing the input signal into several components using non-overlapping sub-sets of the RSTFT coefficients. Sparse representation of signal components is then obtained by inducing L1 regularization penalty on the RSTFT coefficients during the reconstruction phase. The effectiveness of the proposed sparse decomposition method is evaluated in the classification of long-term EEG records for purposes of epileptic seizure detection and sleep stage scoring. Another part of the thesis investigates the detection of seizures in textural images constructed using a proposed scheme for mapping of EEG signals into gray-scale image domain. The proposed mapping strategy makes it plausible to correlate textural changes of the obtained images with seizure activities in EEG records. The textural analysis is then carried out using the well-known gray-level cooccurrence matrix (GLCM) and Haralick’s feature extraction method resulting in a compact representation of EEG epochs. All the methods proposed in this thesis are evaluated using public EEG data-sets freely available on-line. The results obtained by the proposed methods are comprehensively compared with the other conventional dedicated feature extraction techniques using several classifiers. The main contribution of the thesis is in the adaptation of conventional feature extraction techniques, commonly used in the textural analysis of images, to be applicable in EEG signal analysis. Additionally, the discriminatory power of feature descriptors is improved by representing EEG signals using their sparse rational components. The proposed rational local Gabor binary pattern (LGBP)-width feature outperforms competing methods in both seizure detection and classification problems. Moreover, its perform consistency
Case Presentations of the Harvard Affiliated Emergency Medicine Residencies TRICYCLIC ANTIDEPRESSANT OVERDOSE

Q a a r. Pooja Agrawal: Today’s case is that of a 64-year-old oman who was brought in to the Emergency Department y Emergency Medical Services after an apparent suiide attempt. The patient was upset that her husband was till communicating with his ex-wife, who lived in their uilding. After being involved in a verbal altercation ith this woman, the patient stated that she wanted to ie, and subsequently ingested a handful of pills. After uestioning, it was determined that she had taken over 40 ills of 50 mg nortriptylene 2 h before presenting to the mergency Department. She denied ingesting anything lse. She was, at this point, asymptomatic. The past medical history was significant for depresion, hypertension, type 2 diabetes, and mild chronic bstructive pulmonary disease. She had no personal hisory of syncope or coronary disease. The family history as non-contributory; there was no history of sudden nexplained death. Medications included aspirin, chloriazepoxide, hydrochlorthiazide, lisinopril, metformin, someprazole, nortriptyline, tramadol, and simvastatin. here were no recent fevers, illnesses, or trauma. Vital signs were: temperature 36.4°C (97.5°F), heart ate 95 beats/min, blood pressure 160/72 mm Hg, respiatory rate 16 breaths/min, and oxygen saturation 95% on oom air. Initially, the patient appeared agitated and onfused, and subsequently became more somnolent ith shallow breathing. Physical examination revealed o evidence of head injury. Pupils were equal, round, and eactive to light. The neck was supple without meningeal igns. Heart sounds were rapid and regular with no urmurs, rubs, or gallops. The lungs were clear bilaterally o auscultation. The abdomen was soft, with no distenion, tenderness, or guarding. Extremities were warm and ry without rash or swelling. There were no track marks. a
Pengaruh Pemberian Gel Doksisiklin terhadap Jumlah Fibroblas pada Proses Penyembuhan Dermatitis Paederus akibat Racun Kumbang Tomcat (Paederus sp.) pada Mencit (The Effect of Doxycycline Gel on The Number of Fibroblast in Paederus Dermatitis Healing

Paederus dermatitis caused by rove beetle makes the tissue damage called dermonecrosis. The MMP on pederin toxins from the symbiosis of rove beetle (Paederus sp.) and Pseudomonas aeruginosa is supposed can delay the wound healing process. Doxycycline gel as a MMP inhibitor is believed can accelerate the healing process. The purpose of this study was to determine the effect of doxycycline gel on the healing process of Paederus dermatitis by observing the number of fibroblasts as an indicator. This study used 40 mice, were divided into four major groups, those were normal control group, the negative control, treatment groups with doxycycline gel 1% and 5%. Termination was performed on days 1, 3, 5, 7, and 15. Data was obtained by calculating the number of fibroblasts per field of view, then processed in ImageJ and tested statistically with comparation test of One Way Anova. The average number of fibroblasts per field of view in treatment groups was higher. The peak occurred on day 7 and decrease on day 15. It indicated that the topical administration of doxycycline gel on Paederus dermatitis can accelerate healing process, showed by the increasing in average number of fibroblasts per field of view. Keywords : doxycycline gel, fibroblast, paederus dermatitis