Miracle-dz/UniFAR-FTUs huggingface dataset:
Persistent expression of activated notch in the developing hypothalamus affects survival of pituitary progenitors and alters pituitary structure

Background: As the pituitary gland develops, signals from the hypothalamus are necessary for pituitary induction and expansion. Little is known about the control of cues that regulate early signaling between the two structures. Ligands and receptors of the Notch signaling pathway are found in both the hypothalamus and Rathke's pouch. The downstream Notch effector gene Hes1 is required for proper pituitary formation; however, these effects could be due to the action of Hes1 in the hypothalamus, Rathke's pouch, or both. To determine the contribution of hypothalamic Notch signaling to pituitary organogenesis, we used mice with loss and gain of Notch function within the developing hypothalamus. Results: We demonstrate that loss of Notch signaling by conditional deletion of Rbpj in the hypothalamus does not affect expression of Hes1 within the posterior hypothalamus or expression of Hes5. In contrast, expression of activated Notch within the hypothalamus results in ectopic Hes5 expression and increased Hes1 expression, which is sufficient to disrupt pituitary development and postnatal expansion. Conclusions: Taken together, our results indicate that Rbpj‐dependent Notch signaling within the developing hypothalamus is not necessary for pituitary development, but persistent Notch signaling and ectopic Hes5 expression in hypothalamic progenitors affects pituitary induction and expansion. Developmental Dynamics 244:921–934, 2015. © 2015 Wiley Periodicals, Inc.
Skew and slant correction for document images using gradient direction

A fast algorithm is presented for skew and slant correction in printed document images. The algorithm employs only the gradient information. The skew angle is obtained by searching for a peak in the histogram of the gradient orientation of the input grey-level image. The skewness of the document is corrected by a rotation at such an angle. The slant of characters can also be detected using the same technique, and can be corrected by a shear operation. A second method for character slant correction by fitting parallelograms to the connected components is also described. Document images with different contents (tables, figures, and photos) have been tested for skew correction and the algorithm gives accurate results on all the test images, and the algorithm is very easy to implement.
Functional Characterization of a CRH Missense Mutation Identified in an ADNFLE Family

Nocturnal frontal lobe epilepsy has been historically considered a channelopathy caused by mutations in subunits of the neuronal nicotinic acetylcholine receptor or in a recently reported potassium channel. However, these mutations account for only a minority of patients, and the existence of at least a new locus for the disease has been demonstrated. In 2005, we detected two nucleotide variations in the promoter of the CRH gene coding for the corticotropin releasing hormone in 7 patients. These variations cosegregated with the disease and were demonstrated to alter the cellular levels of this hormone. Here, we report the identification in an Italian affected family of a novel missense mutation (hpreproCRH p.Pro30Arg) located in the region of the CRH coding for the protein pro-sequence. The mutation was detected in heterozygosity in the two affected individuals. In vitro assays demonstrated that this mutation results in reduced levels of protein secretion in the short time thus suggesting that mutated people could present an altered capability to respond immediately to stress agents.
1 KALMAN FILTERS

The celebrated Kalman filter, rooted in the state-space formulation of linear dynamical systems, provides a recursive solution to the linear optimal filtering problem. It applies to stationary as well as nonstationary environments. The solution is recursive in that each updated estimate of the state is computed from the previous estimate and the new input data, so only the previous estimate requires storage. In addition to eliminating the need for storing the entire past observed data, the Kalman filter is computationally more efficient than computing the estimate directly from the entire past observed data at each step of the filtering process. In this chapter, we present an introductory treatment of Kalman filters to pave the way for their application in subsequent chapters of the book. We have chosen to follow the original paper by Kalman [1] for the
Weight-Loss Practices and Weight-Related Issues Among Youth With Type 1 or Type 2 Diabetes

OBJECTIVE—The purpose of this study was to describe the weight-loss practices and weight-related issues reported by youth with diabetes, according to sex and diabetes type. RESEARCH DESIGN AND METHODS—A total of 1,742 female and 1,615 male youth aged 10–21 years with type 1 or type 2 diabetes completed a SEARCH for Diabetes in Youth study visit during which height, weight, and A1C were measured. A survey assessed weight-related issues and weight-loss practices. RESULTS—Although more common in youth with type 2 diabetes, youth with type 1 diabetes also reported weight-related concerns and had elevated BMI. Among youth who had ever tried to lose weight (n = 1,646), healthy weight-loss practices (diet [76.5%] and exercise [94.8%]) were the most common, whereas unhealthy practices (fasting [8.6%], using diet aids [7.5%], vomiting or laxative use [2.3%], and skipping insulin doses [4.2%]) were less common. In sex-specific multivariable models including age, race/ethnicity, diabetes type, BMI category, and glycemic control, obese females and overweight/obese males were more likely to report ever practicing any unhealthy weight-loss practice than normal-weight youth. These practices were associated with poor glycemic control for female but not male subjects. All unhealthy weight-loss practices except fasting were more common in female than in male subjects. Dieting, fasting, and using diet aids were all more common in youth with type 2 diabetes than in those with type 1 diabetes. CONCLUSIONS—Given the prevalence of overweight and obesity among youth with type 1 or type 2 diabetes, health care professionals caring for youth with diabetes need to pay particular attention to identifying youth, particularly females, with unhealthy weight-loss practices.
A LogitBoost-Based Algorithm for Detecting Known and Unknown Web Attacks

The rapid growth in the volume and importance of web communication throughout the Internet has heightened the need for better security protection. Security experts, when protecting systems, maintain a database featuring signatures of a large number of attacks to assist with attack detection. However used in isolation, this can limit the capability of the system as it is only able to recognize known attacks. To overcome the problem, we propose an anomaly-based intrusion detection system using an ensemble classification approach to detect unknown attacks on web servers. The process involves removing irrelevant and redundant features utilising a filter and wrapper selection procedure. Logitboost is then employed together with random forests as a weak classifier. The proposed ensemble technique was evaluated with some artificial data sets namely NSL-KDD, an improved version of the old KDD Cup from 1999, and the recently published UNSW-NB15 data set. The experimental results show that our approach demonstrates superiority, in terms of accuracy and detection rate over the traditional approaches, whilst preserving low false rejection rates.
Bi-level Clustering in Telecommunication Fraud

In this paper we describe a fraud detection clustering algorithm applied to the telecom industry. This is an ongoing work that is being developed in collaboration with a leading telecom operator. The choice of clustering algorithms is justified by the need of identifying clients’ abnormal behaviors through the analysis of huge amounts of data. We propose a novel bi-level clustering methodology, where the first level is concerned with the clustering of transactional data and the second level gathers data from the first phase, along with other information, to build high-level clusters.
Use of LysoTracker dyes: A flow cytometric study of autophagy

The flow cytometric use of LysoTracker dyes was employed to investigate the autophagic process and to compare this with the upregulation of autophagy marker, the microtubule‐associated protein LC3B. Although the mechanism of action of LysoTracker dyes is not fully understood, they have been used in microscopy to image acidic spherical organelles, and their use in flow cytometry has not been thoroughly investigated in the study of autophagy. This investigation uses numerous autophagy‐inducing agents including chloroquine (CQ), rapamycin, low serum (<1%) RPMI, and nutrient starvation to induce autophagy in Jurkat T‐cell leukemia and K562 erythromyeloid cell lines. LC3B showed an increase with CQ treatment although this was different to LysoTracker signals in terms of dose and time. Rapamycin, low serum (<1%) RPMI, and nutrient starvation induction of autophagy also induced an increase in LysoTracker and LC3B signals. CQ also induced apoptosis in cell lines, which was blocked by pan‐caspase inhibitor z‐VAD resulting in a reduction in cells undergoing apoptosis and a subsequent upregulation of autophagic markers LC3B and lysosomal dye signals. Given that LC3B and LysoTracker are measuring different biological events in the autophagic process, they surprisingly both upregulated during autophagic process. This study, however, shows that although LysoTracker dyes do not specifically label lysosomes or autophagosomes within the cell, they allow the simultaneous measurement of an autophagy‐related process and other live‐cell functions, which are not possible with the standard LC3B antibody‐labeling technique. This method has the advantage of other live‐cell LCB‐GFP‐tagged experiments in that be used to analyze patient cells as well as easier to use and significantly less costly. © 2013 International Society for Advancement of Cytometry
Face recognition using kernel direct discriminant analysis algorithms

Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition (FR) systems. It is well known that the distribution of face images, under a perceivable variation in viewpoint, illumination or facial expression, is highly nonlinear and complex. It is, therefore, not surprising that linear techniques, such as those based on principle component analysis (PCA) or linear discriminant analysis (LDA), cannot provide reliable and robust solutions to those FR problems with complex face variations. In this paper, we propose a kernel machine-based discriminant analysis method, which deals with the nonlinearity of the face patterns' distribution. The proposed method also effectively solves the so-called "small sample size" (SSS) problem, which exists in most FR tasks. The new algorithm has been tested, in terms of classification error rate performance, on the multiview UMIST face database. Results indicate that the proposed methodology is able to achieve excellent performance with only a very small set of features being used, and its error rate is approximately 34% and 48% of those of two other commonly used kernel FR approaches, the kernel-PCA (KPCA) and the generalized discriminant analysis (GDA), respectively.
Explicit Conjunctions without Compilation: Computing hFF(PiC) in Polynomial Time

A successful partial delete relaxation method is to compute hFF in a compiled planning task PiC which represents a set C of conjunctions explicitly. While this compilation view of such partial delete relaxation is simple and elegant, its meaning with respect to the original planning task is opaque. We provide a direct characterization of h+(PiC), without compilation, making explicit how it arises from a "marriage" of the critical-path heuristic hm with (a somewhat novel view of) h+. This explicit view allows us to derive a direct characterization of hFF(PiC), which in turn allows us to compute a version of that heuristic function in time polynomial in |C|.
Does Child Abuse Cause Crime?

Child maltreatment, which includes both child abuse and child neglect, is a major social problem. This paper focuses on measuring the effects of child maltreatment on crime using data from the National Longitudinal Study of Adolescent Health (Add Health). We focus on crime because it is one of the most socially costly potential outcomes of maltreatment, and because the proposed mechanisms linking maltreatment and crime are relatively well elucidated in the literature. Our work addresses many limitations of the existing literature on child maltreatment. First, we use a large national sample, and investigate different types of abuse in a similar framework. Second, we pay careful attention to identifying the causal impact of abuse, by using a variety of statistical methods that make differing assumptions. These methods include: Ordinary Least Squares (OLS), propensity score matching estimators, and twin fixed effects. Finally, we examine the extent to which the effects of maltreatment vary with socio-economic status (SES), gender, and the severity of the maltreatment. We find that maltreatment approximately doubles the probability of engaging in many types of crime. Low SES children are both more likely to be mistreated and suffer more damaging effects. Boys are at greater risk than girls, at least in terms of increased propensity to commit crime. Sexual abuse appears to have the largest negative effects, perhaps justifying the emphasis on this type of abuse in the literature. Finally, the probability of engaging in crime increases with the experience of multiple forms of maltreatment as well as the experience of Child Protective Services (CPS) investigation.
Simple Scoring Scheme for Calculating the Risk of Acute Coronary Events Based on the 10-Year Follow-Up of the Prospective Cardiovascular Münster (PROCAM) Study

Background—The absolute risk of an acute coronary event depends on the totality of risk factors exhibited by an individual, the so-called global risk profile. Although several scoring schemes have been suggested to calculate this profile, many omit information on important variables such as family history of coronary heart disease or LDL cholesterol. Methods and Results—Based on 325 acute coronary events occurring within 10 years of follow-up among 5389 men 35 to 65 years of age at recruitment into the Pro spective Ca rdiovascular Mü nster (PROCAM) study, we developed a Cox proportional hazards model using the following 8 independent risk variables, ranked in order of importance: age, LDL cholesterol, smoking, HDL cholesterol, systolic blood pressure, family history of premature myocardial infarction, diabetes mellitus, and triglycerides. We then derived a simple point scoring system based on the &bgr;-coefficients of this model. The accuracy of this point scoring scheme was comparable to coronary event prediction when the continuous variables themselves were used. The scoring system accurately predicted observed coronary events with an area under the receiver-operating characteristics curve of 82.4% compared with 82.9% for the Cox model with continuous variables. Conclusions—Our scoring system is a simple and accurate way of predicting global risk of myocardial infarction in clinical practice and will therefore allow more accurate targeting of preventive therapy.
Fully Dynamic Shortest-Path Distance Query Acceleration on Massive Networks

The distance between vertices is one of the most fundamental measures for representing relations between them, and it is the basis of other classic measures of vertices, such as similarity, centrality, and influence. The 2-hop labeling methods are known as the fastest exact point-to-point distance algorithms on million-scale networks. However, they cannot handle billion-scale networks because of the large space requirement and long preprocessing time. In this paper, we present the first algorithm that can process exact distance queries on fully dynamic billion-scale networks besides trivial non-indexing algorithms, which combines an online bidirectional breadth-first search (BFS) and an offline indexing method for handling billion-scale networks in memory. First, we accelerate bidirectional BFSs by using heuristics that exploit the small-world property of complex networks. Then, we construct bit-parallel shortest-path trees to maintain sets of shortest paths passing through high-degree vertices of networks in compact form, the information of which enables us to avoid visiting vertices with high degrees during bidirectional BFSs. Thus, the searches achieve considerable speedup. In addition, our index size reduction technique enables us to handle billion-scale networks in memory. Furthermore, we introduce dynamic update procedures of our data structure to handle fully dynamic networks. We evaluated the performance of the proposed method on real-world networks. In particular, on large-scale social networks with over 1B edges, the proposed method enables us to answer distance queries in around 1 ms, on average.
Low-cost 360 stereo photography and video capture

A number of consumer-grade spherical cameras have recently appeared, enabling affordable monoscopic VR content creation in the form of full 360° X 180° spherical panoramic photos and videos. While monoscopic content is certainly engaging, it fails to leverage a main aspect of VR HMDs, namely stereoscopic display. Recent stereoscopic capture rigs involve placing many cameras in a ring and synthesizing an omni-directional stereo panorama enabling a user to look around to explore the scene in stereo. In this work, we describe a method that takes images from two 360° spherical cameras and synthesizes an omni-directional stereo panorama with stereo in all directions. Our proposed method has a lower equipment cost than camera-ring alternatives, can be assembled with currently available off-the-shelf equipment, and is relatively small and light-weight compared to the alternatives. We validate our method by generating both stills and videos. We have conducted a user study to better understand what kinds of geometric processing are necessary for a pleasant viewing experience. We also discuss several algorithmic variations, each with their own time and quality trade-offs.
Programming language optimizations for modular router configurations

Networking systems such as Ensemble, the x-kernel, Scout, and Click achieve flexibility by building routers and other packet processors from modular components. Unfortunately, component designs are often slower than purpose-built code, and routers in particular have stringent efficiency requirements. This paper addresses the efficiency problems of one component-based router, Click, through optimization tools inspired in part by compiler optimization passes. This pragmatic approach can result in significant performance improvements; for example, the combination of three optimizations reduces the amount of CPU time Click requires to process a packet in a simple IP router by 34%. We present several optimization tools, describe how those tools affected the design of Click itself, and present detailed evaluations of Click's performance with and without optimization.
Acute Renal Failure : Causes and Prognosis MOST FREQUENT CAUSES OF ACUTE TUBULOINTERSTITIAL NEPHRITIS Antimicrobials Penicillin Ampicillin

There are many causes—more than fifty are given within this present chapter—that can trigger pathophysiological mechanisms leading to acute renal failure (ARF). This syndrome is characterized by a sudden decrease in kidney function, with a consequence of loss of the hemostatic equilibrium of the internal medium. The primary marker is an increase in the concentration of the nitrogenous components of blood. A second marker, oliguria, is seen in 50% to 70% of cases. In general, the causes of ARF have a dynamic behavior as they change as a function of the economical and medical development of the community. Economic differences justify the different spectrum in the causes of ARF in developed and developing countries. The setting where ARF appears (community versus hospital), or the place where ARF is treated (intensive care units [ICU] versus other hospital areas) also show differences in the causes of ARF. While functional outcome after ARF is usually good among the surviving patients, mortality rate is high: around 45% in general series and close to 70% in ICU series. Although it is unfortunate that these mortality rates have remained fairly constant over the past decades, it should be noted that today’s patients are generally much older and display a generally much more severe condition than was true in the past. These age and severity factors, together with the more aggressive therapeutical possibilities presently available, could account for this apparent paradox. As is true for any severe clinical condition, a prognostic estimation of ARF is of great utility for both the patients and their families, the medical specialists (for analysis of therapeutical maneuvers and options), and for society in general (demonstrating the monetary costs of treatment). This chapter also contains a brief review of the prognostic tools available for application to ARF. Fernando Liaño Julio Pascual
Small Airway Impairment and Bronchial Hyperresponsiveness in Asthma Onset

Purpose Our study tried to find a relationship between baseline FEF25-75% and airway hyperresponsiveness (AHR) and whether a greater FEF25-75% impairment may be a marker of a more severe hyperresponsiveness in subjects with normal FEV1 and FEV1/FVC and suggestive asthma symptoms. Besides, we tried to asses a FEF25-75% cut-off value to identify hyper-reactive subjects. Methods 4,172 subjects (2,042 M; mean age: 38.3±14.9; mean FEV1 % predicted: 100.5±12.7 and FEV1/FVC: 85.4±6.8) were examined after performing a methacholine (Mch) test. All subjects reported a symptom onset within 3 years before the test. Subjects with PD20<400 or >400 µg were arbitrarily considered affected by moderate/severe and borderline AHR, respectively. Results PD20 values were 213 (IQR:86-557), 340 (IQR:157-872) and 433 (IQR:196-1032) µg in subjects with baseline FEF25-75≤50%, FEF25-75 between 50 and 70% and FEF25-75>70% respectively (P<0.0001). Only in moderate/severe hyper-reactive subjects (excluded borderlines), PD20 was lower in the FEF25-75≤50% subgroup than in the 1 with FEF25-75>70%. The hyperreactive subjects percentage, was higher in those with FEF25-75≤50% and lower in those with FEF25-75>70% (P<0.0001). FEF25-75<50% (compared to FEF25-75>70%) was a higher AHR risk factor, especially in subjects with moderate/severe AHR (OR: 2.18 [IQR:1.41-3.37]; P<0.0001). Thresholds yielding the highest combined sensitivity/specificity for FEF25-75% were 75.19 (area under curve [AUC]: 0.653) and 74.95 (AUC:0.688) in subjects with PD20<2,400 and <400 µg respectively. FEV1, FVC, and FEV1/FVC measured in subjects with different FEF25-75≤50%, FEF25-75>50 and ≤70% or FEF25-75>70% levels were similar both in normoreactive and hyperreactive subjects. Conclusions At asthma onset, reduced baseline FEF25-75 values with normal FEV1 and FEV1/FVC may predict AHR. Detectable predictive cut-off values do not exist because even normoreactive subjects can show lower FEF25-75 values. Furthermore, a greater FEF25-75 reduction may be associated to a more severe AHR, suggesting a possible FEF25-75 role in the management of asthma when FEV1 and FEV1/FVC are normal.