Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Platelet Rich Plasma in Treatment of Androgenetic Alopecia (AGA): An Interventional Study

Androgenetic alopecia (AGA) is a common condition having severe psychosocial implications. Numerous modalities of treatment are there but none is satisfactory both to the patient and the treating physician. This present study was carried out on 50 patients of AGA aged between 20 to 50 years to find out the effect of PRP with micro needling on AGA. These selected cases were treated by activation of the procedure site (scalp) by micro needling technique and application of platelet rich plasma on the activated site. A total of 6 such sittings were given to each patient at interval of 30 days each, over a total period of 6 months. Macro photographs were taken at baseline and after 6 months by 2 independent observers who rated those using of standardized seven-point rating scale of clinical change. In this study, 24% patients perceived stoppage of hair fall, 68% patients noticed reduction in hair fall, 6% of the patients perceived no change in hair fall and remaining 2% patients perceived increased hair fall after last visit with minimal or no side effects. So over all 92% patients had noticed some clinical improvement in their condition. So it was concluded that PRP with micro needling is an effective combination in treating AGA. This may be because micro needling has its own action and it would also help in promoting penetration of PRP but the level of evidence of this fact as available published data is low. This demands further studies to gain more evidence before it is used more extensively. Keyword: Androgenetic Alopecia(AGA), Platelet Rich Plasma (PRP), Micro Needling.
Data-Driven Evaluation Metrics for Heterogeneous Search Engine Result Pages

Evaluation metrics for search typically assume items are homoge- neous. However, in the context of web search, this assumption does not hold. Modern search engine result pages (SERPs) are composed of a variety of item types (e.g., news, web, entity, etc.), and their influence on browsing behavior is largely unknown. In this paper, we perform a large-scale empirical analysis of pop- ular web search queries and investigate how different item types influence how people interact on SERPs. We then infer a user browsing model given people's interactions with SERP items - creating a data-driven metric based on item type. We show that the proposed metric leads to more accurate estimates of: (1) total gain, (2) total time spent, and (3) stopping depth - without requiring extensive parameter tuning or a priori relevance information. These results suggest that item heterogeneity should be accounted for when de- veloping metrics for SERPs. While many open questions remain concerning the applicability and generalizability of data-driven metrics, they do serve as a formal mechanism to link observed user behaviors directly to how performance is measured. From this approach, we can draw new insights regarding the relationship between behavior and performance - and design data-driven metrics based on real user behavior rather than using metrics reliant on some hypothesized model of user browsing behavior.
Exchange Rate and Consumer Prices in Mozambique: A cointegration Approach

Using monthly data from 2001:1 to 2006:12, this paper applies the cointegration approach and the associated error correction model to study the importance of money, exchange rate and South African prices in explaining consumer price changes in Mozambique, focusing on the estimation of the long-run pass-through coefficient. Consistent with previous research, the paper finds that money, the exchange rate and inflation are important determinants of inflation in Mozambique. In particular, one per cent exchange rate depreciation leads to 0.15 per cent increase in the price level. In addition, money and the South African prices are the most important variables in explaining the variation in prices. Compared with the exchange rate, money explains a relatively larger variation in prices but its relative importance seems to have diminished.
All Fun and Games: Obtaining Critical Pedestrian Behavior Data from an Online Simulation

Automated cars will need to observe pedestrians and react adequately to their behavior when driving in urban areas. Judging pedestrian behavior, however, is hard. When approaching it by machine learning methods, large amounts of training data is needed, which is costly and difficult to obtain, especially for critical situations. In order to provide such data, we have developed an online game inspired by Frogger, in which players have to cross streets. Accidents and critical situations are a natural part of the data produced in such a way without anybody getting hurt in reality. We present the design of our game and an analysis of the resulting data and its match to real world behavior observed in previous work. We found that behavior patterns in real and virtual environments correlated and argue that game data could be used to train machine learning algorithms for predicting real pedestrians' walking trajectories when crossing a road. This approach could be used in future automated vehicles to increase pedestrian safety.
Unsupervised Multi-Label Image and Texture Segmentation based on Optimal Feature Representation

In this paper, an adaptive and robust unsupervised texture segmentation algorithm is proposed. One of the novelties of this proposed algorithm is to determine optimal sub-image size by pattern analysis and another one is optimizing segmentation process by providing the most successful representation of pattern on images. The realization of the algorithm consists of various stages. Firstly, the parameters of regional minima and maxima for images are obtained to extract real pattern information about images. In the next stage, these outputs are combined to each other to calculate the centroid of distribution of patterns. The input image and several texture analysis features are analyzed in the light of this pattern information. Then, the dimension reduction process is performed by the PCA with Horn's parallel analysis method before the data clustering is applied to the dataset. This method allows optimal representation of data after dimension reduction process. The output image is improved by subjecting it to various morphological operations which are called an adaptive morphological mask and the performance of the proposed algorithm is compared with other texture segmentation algorithms.
Development and validation of the humanitarian aid workers resilience scale (HAWRS)

Background: Humanitarian aid workers experience various challenges in disasters, which affects their wellbeing. Being resilience can help volunteers to adapt to them. This study was conducted to develop and validate a resiliency questionnaire to evaluate the resilience of humanitarian aid workers in disasters. Methods: This study was conducted in 2 phases between Dec 2017 and Oct 2018. In the first phase for item generation, we used qualitative content analysis. Face-to-face semi-structured interviews with 18 humanitarian aid workers were used for data collection. In the second phase, by conducting a quantitative study, the psychometric properties of the scale including face, content and construct validities as well as internal and external reliabilities, were determined. Data analysis was performed using SPSS 19 and the significance level was set at less than 0.05. Results: Six main subjects were extracted from the first-stage data using content analysis. The final questionnaire included six factors and 31 items after validity and reliability criteria analysis. These six factors including organizational supports, individual factors, organizational planning, social support, teamwork and challenges of disaster scene included 52.19% of the variance. The internal consistency was confirmed as well (Cronbach’s alpha = 0.814). Conclusion: This specific self-assessment questionnaire can be used for scoring the resilience of humanitarian aid workers in disasters. In the case of low resilience score of volunteers, managers should avoid sending them on missions and try to improve their resilience through educational programs.
Machine Learning in Computer Vision and Natural Language Processing

Most research in text classification has been done under a closed world assumption. That is, the classifier is tested with unseen examples of the same classes that it was trained with. However, in most real world scenarios, we come across novel data that do not belong to any of the known classes, and hence should not ideally be categorized correctly by the classifier. The goal of open world classifiers is to anticipate and be ready to handle test examples of classes unseen during training. The classifier can simply declare that a test example belongs to an unknown class, or alternatively, incorporate it into its knowledge as an example of a new class it has learned. Although substantial research has been done in open world image classifiers, its applications in text classification is yet to be explored thoroughly. Keywords—open-set classification, text classification, convolutional neural networks, deep learning, outlier ensembles, isolation forest, weibull distribution
Nonhuman Primates and Humanized Mice for Studies of HIV-1 Integrase Inhibitors: A Review

Since the discovery of the first inhibitors of HIV replication, drug resistance has been a major problem in HIV therapy due in part to the high mutation rate of HIV. Therefore, the development of a predictive animal model is important to identify impending resistance mutations and to possibly inform treatment decisions. Significant advances have been made possible through use of nonhuman primates infected by SIV, SHIV, and simian-tropic HIV-1 (stHIV-1), and use of humanized mouse models of HIV-1 infections. In this review, we describe some of the findings from animal models used for the preclinical testing of integrase strand transfer inhibitors. These models have led to important findings about the potential role of integrase strand transfer inhibitors in both the prevention and treatment of HIV-1 infection.
ESTIMATING AN EQUILIBRIUM MODEL OF LIMIT ORDER MARKETS

I estimate an equilibrium model using limit order data, finding parameters that describe information and liquidity preferences for trading. As a case study, I estimate the model for Google stock surrounding an unexpected good-news earnings announcement in the 3rd quarter of 2009. I find a substantial decrease in asymmetric information prior to the earnings announcement. I also simulate counterfactual dealer markets and find empirical evidence that limit order markets perform more efficiently than do their dealer market counterparts.
CD34-Negative is Highly Associated with T (15;17), T (V; 11q23) and theNPM1-Mutation Subtypes in 343 Newly Diagnosed Patients with Acute MyeloidLeukemia

Objective: Recent reports found that several cytogenetic or molecular subtypes of acute myeloid leukemia (AML) are associated with CD34-positive. However, the status of CD34-negative in AML needs to be explored. In this study, we aimed to explore the prevalence of the CD34-negative patients and its association with molecular genetics status in a large consecutive AML cohort. Methods: A group of 343 consecutive newly diagnosed AML patients was retrospectively analyzed in our center. CD34 expression was detected by flow cytometry and considered negative when it was expressed in less than 20% of the bone marrow blast cells. The karyotype was analyzed by the G-banding technique. Leukemic fusion genes and mutated genes were detected by PCR method. Results: CD34-negative was found in 143 (41.7%) of the 343 patients. According to FAB classification, the percentages of CD34-negative patients were higher in the M3 and M5 (100% and 70%, respectively) and lower in the M2 and M4 subtypes (30.3% and 21.2%, respectively). According to the WHO classification, the percentage of CD34-negative patients was higher in those with t(15; 17), t(v; 11q23), and the NPM1-mutation (100%, n=37; 100%, n=7; and 81.7%, n=71, respectively) and lower in those with t(8;21) and AML with MDS-related changes (8.6%, n=35 and 5.0%, n=20, respectively). The patients with t(15; 17), t(v; 11q23) and the NPM1-mutation consisted of 71.3% (102/143) of the CD34-negative population and 6.5% (13/200) of the CD34-positive population (p<0.0001). A CD34-negative phenotype was associated with risk subgroups according to cytogenetics alone and when combining cytogenetics and molecular analysis (p=0.025 and p<0.0001, respectively). The sensitivity, specificity, positivepredictive value and negative-predictive value of the CD34-negative to t (15;17), t (v; 11q23) and the NPM1-mutation were 88.7%, 82.0%, 71.3% and 93.5%, respectively. Conclusions: The prevalence of the CD34-negative patients is very common in newly diagnosed AML. CD34- negative is highly associated with t (15;17), t(v; 11q23) and the NPM1-mutation in AML patients, which provide the evidence about the association of immunophenotype and molecular genetics.
CAT(0) metrics on contractible manifolds

We prove that an open manifoldM of dimension at least 5 which admits a complete CAT(0) polyhedral metric is pseudo-collarable, its fundamental group at infinity is strongly perfectly semistable and has vanishing ChapmanSiebenmann obstruction τ∞(M). Moreover, this implies that M is topologically collapsible, when n ≥ 6. Conversely, any finite dimensional collapsible polyhedron is PL homeomorphic to a CAT(0) cubical complex.
CYTOLOGICAL CHARACTERISTICS OF POSTOPERATIVE METASTASES OF PAPILLARY THYROID CANCER DURING THE DEVELOPMENT OF SECONDARY RADIOIODINE REFRACTORINESS

Radioiodine refractoriness is the main problem in the diagnosis and treatment of papillary thyroid carcinoma. The aim of the study was to investigate the cytological and immunocytochemical changes of thyrocytes in fine-needle aspiration smears of thyroid papillary cancer metastases in the course of the development of secondary radioiodine resistance. A total of 70 postoperative metastases of thyroid papillary cancer (secondary radioiodine refractory metastases, previously responsive to radioiodine, that eventually loses the ability to radioiodine accumulation, radioiodine-avid metastases, primary radioiodine-refractory metastases), immunohistochemical staining of thyroid peroxidase, thyroglobulin, cytokeratin 17 and cytological analysis were performed. Revealing the presence of specific cellular phenotypes and structures in punctuates, a low percentage of thyroid peroxidase and thyroglobulin-positive thyrocytes allows the development of the method of cytological prediction of the radioiodine therapy effectiveness.
Efficacy of Seed Priming on Yield and Yield Attributing Characters in French Bean (Phaseolus Vulgaris L.)

Seed is the integral factor in crop production. From the time immemorial seed quality is regarded as a cardinal element in the development of Agriculture and evidences of this has been observed in old Vedic literatures. In Manu Smriti it is mentioned that “Subeejam Sukshetre Jayate Sampadyathe” that means good seed in good soil yields abundantly. The requisite for good quality seed for increased production was International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 2 (2020) Journal homepage: http://www.ijcmas. com
Poly(3-hexylthiophene-2,5-diyl) regioregular (P3HT) thin film as saturable absorber for passively Q-switched and mode-locked Erbium-doped fiber laser

Q-switched and mode-locked Erbium-doped fiber lasers (EDFLs) were demonstrated using poly(3-hexylthiophene-2,5-diyl) regioregular (P3HT) organic semiconductor in the form of thin film as a saturable absorber (SA). The P3HT thin film is cut into small pieces and sandwiched between two ferrules in EDFL cavity to generate a stable Q-switching and mode-locking pulse train. By increasing the 980 nm pump power from 63mW to 125mW, the repetition rate of the EDFL increases from 62.97 kHz to 78.63 kHz while the pulse width decreases from 5.52 μs to 3.79 μs. The maximum pulse energy of 15.05 nJ is generated with repetition rate and pulse width of 78.63 kHz and 3.79 μs, respectively. Meanwhile, self-starting mode-locked EDFL arises as the pump power raises from 125mW to 187mW. As the pump power increases to the maximum, the repetition rate is almost constant of 1.838MHz and pulse width of 2.62 ps are observed. The mode-locked EDFL operated at 1563 nm wavelength. This experiment shows that P3HT SA can be used to generate stable Q-switched and mode-locked pulsed lasers.
Foliar Diagnostic Norms for Litchi (Litchi chinensis Sonn) in Lower Himalayas

Litchi (Litchi chinensis Sonn.) is an important fruit crop belonging to the family Sapindaceae. In Uttarakhand, litchi is an important subtropical fruit crop after the mango. It is also known as queen of the fruits due to its attractive deep pink/red colour and fragrant aril. Litchi is a delicious fruit having aromatic pulp with sweet and slightly acidic taste. Litchi is largely preferred as table fruit. It is also used for canning, which has impact in International trade as well. ‘Litchi Nut’ a dried product of whole litchi fruit is also potential product worldwide. High quality, flavoured squashes can also be prepared from litchi. Commercial litchi plantation creates ‘a source of job opportunity’ for the people associated with growing and managing orchards, harvesting and post-harvest International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 2 (2020) Journal homepage: http://www.ijcmas. com
PROLEGIS: Intelligent Search in Legislation Databases

—Portuguese legislation, similarly to other countries, is not published in an organized way, being it by topics or concepts. Instead, it is organized by a numbering system which follows the publication order. For a common citizen or even researchers, searching for information about a subject or a speciﬁc problem is an hard and complex task. The categorization of legal texts, besides requiring specialized labour, is a task which would need a great amount of time due to the quantity of published documents. Because of that, the Text Categorization (TC) task often relies on Machine Learning (ML) algorithms. Thefocus of this work will be on the supervised domain, nevertheless, an unsupervised clustering analysis is also explored. Multiple supervised classiﬁcation algorithms are experimented, using a set of pre-classiﬁed documents, in order to comparatively evaluate their classiﬁcation performances. Support Vector Machines, K-Nearest Neighbours, Multinomial Naive Bayes and Decision-Trees were used individually and, in order to seek to enhance the results, in conjunction with various techniques for pre-processing features. Latent Semantic Indexing, feature selection with different metrics and stemming were analysed.
Winnowing with Gradient Descent

We rewrite the non-negative weights wi of multiplicative updates by ρ 2 i and replace the multiplicative updates by a gradient descent step w.r. t. the new parameter ρi. We do this for the Winnow update, the Hedge update, and the unnnormalized and normalized exponentiated gradient (EG) updates for linear regression. When the original weights wi are scaled to sum to one (as done for Hedge and normalized EG), then in the corresponding reparameterized update, the ρi parameters are now divided by 1/‖ρ‖2 after the gradient descent step. We show that the reparameterizations closely track the original multiplicative updates by proving the same online regret bounds in each case (albeit in some cases with slightly worse constants). In particular, our work implies that the typical logarithmic dependence in the number of features of the multiplicative updates for sparse targets can also be achieved with the reparameterized gradient descent updates. As a side, our work exhibits a simple linear 2-layer neural net that when trained with gradient descent can provable solve a certain sparse linear problem (known has the Hadamard problem) with exponentially fewer examples than any kernel method. The talk will stay at a high level. In particular we will discuss the implication of these results on the power of neural nets versus kernel methods and on the influence of the training algorithm for neural nets. We conclude with a number of fundamental open problems. Most of the presented work work was done jointly with Ehsan Amid.
COMIENZO DE TRATAMIENTO RENAL SUSTITUTIVO EN LA PROVINCIA DE CACERES

RESUMEN Introduccion: La derivacion precoz al nefrologo y el inicio programado de dia-lisis se asocian a un mejor pronostico tras el comienzo del tratamiento renal sus-titutivo (TRS). El objetivo de nuestro estudio fue analizar las caracteristicas clini-cas y analiticas de los pacientes al comienzo de dialisis y valorar si el inicioprogramado influia en la morbi-mortalidad a los 6 meses. Pacientes y metodos: Estudio retrospectivo que incluye los 117 pacientes queiniciaron TRS en nuestra provincia en los anos 2003-2004 (47 mujeres y 70 va-rones). Se revisaron las caracteristicas demograficas,los datos clinicos y analiticosal inicio,los ingresos hospitalarios y la mortalidad a los 6 meses.Los pacientes sedividieron en programados (P) y no programados (NP) dependiendo si la prime-ra dialisis se realizo en situacion de urgencia (NP) o si pudo ser diferida en eltiempo mas de 24 horas (P). Resultados: Sesenta y cinco pacientes comenzaron TRS de forma programada(56,4%) y 52 de forma no programada (43,6%). Los pacientes P presentaban ac-ceso vascular o peritoneal util en un porcentaje mayor (83,1%
What is Better? A Preliminary Investigation of Between-Session Change

Several studies of pre-treatment change (PTC) have appeared in the solution-focused literature. Less information and virtually no studies have appeared on the topic of between-session change (BSC) in the solution-focused literature. This study sought to determine the percentage of clients reporting positive, treatment-related gains between sessions of solution-focused brief therapy. Nearly 80% of the total sample indicated that some improvement had taken place between visits by the end of the session. However, 24% of the clients answered that nothing was better from session to session of solution-focused therapy when asked at the beginning of the visit. Of these, only 13% (4/31) went on to report change via the scaling question by the end of the visit. This latter result is significantly different than findings from previous studies on change in solution-focused therapy. Implications for research and practice are discussed.
PREVALÊNCIA DE DIABETES MELLITUS E PRÁTICA DE EXERCÍCIO EM INDIVÍDUOS QUE PROCURARAM ATENDIMENTO NA ESTRATÉGIA SAÚDE DA FAMÍLIA DE VIÇOSA/MG PREVALENCE OF DIABETES MELLITUS AND EXERCISE PRACTICE IN INDIVIDUALS WHO SOUGHT CARE AT THE FAMILY HEALTH STRATEGY OF VIÇOSA/MG

O objetivo do estudo foi verificar a prevalencia de diabetes mellitus (DM) em individuos que procuraram atendimento na ESF, assim como, a pratica de exercicios fisicos entre os pacientes diagnosticados com DM, de acordo com sexo e faixa etaria. Avaliaram-se informacoes sobre DM e pratica de exercicio de 11392 usuarios atendidos por quatro Unidades Basicas de Saude do municipio de Vicosa/MG, por meio das