Miracle-dz/UniFAR-FTUs huggingface dataset:
Non Surgical Disc Decompression & Clinical Efficacy

The standard medical approach to back pain currently is prescribing analgesic, anti-inflammatory drugs, muscle relaxant and sometimes morphine derivatives. This is often not very effective. “Medical care for low back pain in the 20th century was catastrophic. Most approach did not solved the daily symptoms of lower back pain and may even have reinforced and exacerbated the problem,” Gordon Waddell, MD, orthopedic surgeon and researcher of the spine [1].
Efficient Methods to Trigger Adversarial Behaviors from Malware during Virtual Execution in SandBox

Recently, various organizations are confronting a grater attack surface, the growing proliferation of malware and the number of malicious codes has been consistently growing for several years. To respond actively against these malicious codes, analysts employ automated investigation tools on the malware. However, there has been advent of malware employing the various techniques to avoid the detection of the SandBox, which makes hard to identify the adversarial behaviors of the samples codes. In this paper, we propose efficient methods to trigger adversarial behaviors from the sample codes during virtual execution in the Sandbox in order to perform the analysis of malware.
Update on Clinical and Epidemiological Features of Viral Hepatitis A

HAV is a very resistant virus in the environment because of by the absence of envelop. The virus is resistant against denaturation by drying, temperature as high as 56°C and as low as -20°C and acid at pH 3.0 [3,5,6]. The virus can also survive in used water for weeks at 20 °C temperature especially if the humidity is low. The virus is neutralized after heating at 70 °C for 4 min and inactivated by radiation, by the glutaraldehyde 2%, formaldehyde and bleach reconstituted and diluted at 1/5 [5,7].
Optimizing three phase current regulators for low inductance loads

In this paper, a new space vector based predictive current regulator is proposed which is suitable for operation with low inductance loads such as high speed motor drives with low inductances particularly for electric vehicle applications, high dynamic response servo and vector controlled motor drives, voltage source inverters-VSIs-connected to utility grids and interconnected UPS systems with active damping requirements, and for nonsinusoidal current tracking applications such as for active filters. The proposed predictive current regulator achieves: constant switching frequency by using a carrier based space vector voltage PWM switching strategy, minimizes both high and low frequency current errors and can operate with extremely low load inductances of typically <5%. This implies that good spectral performance and spectral separation is maintained at light loads and enables the proposed current regulator to achieve insensitivity to load inductance. The paper presents a new analog modulator implementation and includes a simulated and experimental validation of the proposed predictive current regulator for sinusoidal and nonsinusoidal current tracking with low inductance loads.
Combination methods for ensembles of multilayer feedforward

As shown in the bibliography, training an ensemble of networks is an interesting way to improve the performance with respect to a single network. The two key factors to design an ensemble are how to train the individual networks and how to combine the different outputs of the networks to give a single output class. In this paper, we focus in the combination methods. We study the performance of fourteen different combination methods for ensembles of the type "simple ensemble" and "decorrelated". In the case of the "simple ensemble" and low number of networks in the ensemble, the method Zimmermann gets the best performance. When the number of networks is in the range of 9 and 20 the weighted average is the best alternative. Finally, in the case of the ensemble "decorrelated" the best performing method is averaging over a wide spectrum of the number of networks in the ensemble.
Cognitive Processes of Students Participating in Engineering-focused Design Instruction

Introduction Since the publication of the Standards for Technological Literacy in 2000 (ITEA), there have been a number of new programs developed that are designed to teach pre-engineering. Project Lead the Way is one such program. Project Lead the Way boasts serving over 1250 schools in 44 states and teaching over 160,000 students (McVearry, 2003). Efforts are also being made to infuse engineering design into technology education programs. One example of this is the work of the National Center for Engineering and Technology Education (NCETE) partnering with high school technology educators in summer inservice workshops to help teachers develop activities and curriculum to instill engineering design into technology education programs. According to Douglas, Iversen, & Kalyandurg (2004), the engineering community has identified the need for teaching engineering in K-12, and this has been supported by the American Society of Engineering Education (ASEE). The ASEE research analyzed the current practices of K-12 engineering education. The study stated: Clearly, there is a societal argument for the need for engineering education in our K-12 classrooms, as technical literacy promotes economic advancement. There is a statistical argument, as the number of students entering engineering schools declines, related to overall enrollment, and the number of women and underrepresented minorities in engineering remains well below the national average for higher education (Douglas, Iversen, & Kalyandurg, 2004, p. 3).
The efficiency of CT at pre-operative evaluation stage of PCI in patients with recurrent ovarian cancer

Poster: "ECR 2017 / C-3086 / The efficiency of CT at pre-operative evaluation stage of PCI in patients with recurrent ovarian cancer" by: "O. Hural, Y. Mylyan, M. Fetsych, R. Yarema; Lviv/UA"
Auricular Acupuncture for Post-Operative Tonsillectomy Pain Management

Battlefield acupuncture is a quickly taught auricular acupuncture technique, where semi-permanent acupuncture needles are placed on five specific points on the ear for acute pain relief. Pain management after tonsillectomy can be problematic. Postoperative pain restricts drinking and eating, and increases postoperative morbidity slowing recovery. Increasing evidence indicates that acupuncture has a role in post-operative tonsillectomy pain management. With auricular acupuncture, specific auricular acupuncture points are stimulated using a variety of methods that can include small needles, seeds and magnets. These devices can be left temporarily in place using adhesive tape. The patient or parent can then repeatedly apply pressure to the acupoints for several minutes a day for ongoing pain relief, which allows the patient to have continued acupuncture benefits in a home environment. Acupuncture has the advantages of low cost, few complications and minimal adverse side effects. Auricular acupuncture could potentially decrease analgesic consumption and its potential adverse effects, promoting early recovery. Auricular acupuncture could add a further option to post-tonsillectomy surgical pain management.
Mapping urban land cover based on spatial-spectral classification of hyperspectral remote-sensing data

ABSTRACT In this article, an innovative classification framework for hyperspectral image data, based on both spectral and spatial information, is proposed. The main objective of this method is to improve the accuracy and efficiency of high-resolution land-cover mapping in urban areas. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MMSF) algorithm. A pixel-based support vector machine (SVM) algorithm is first used to classify the hyperspectral image data, then the enhanced MMSF algorithm is applied in order to increase the accuracy of less accurately classified land-cover types. The enhanced MMSF algorithm is used as a binary classifier. These two classes are the low-accuracy class and remaining classes. Finally, the SVM algorithm is trained for classes with acceptable accuracy. In the proposed approach, namely MSF-SVM, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithms, and are then used to build the MSF. Three benchmark hyperspectral data sets are used for the assessment: Berlin, Washington DC Mall, and Quebec City. Experimental results demonstrate the superiority of the proposed approach compared with SVM and the original MMSF algorithms. It achieves approximately 5, 6, and 7% higher rates in kappa coefficients of agreement in comparison with the original MMSF algorithm for the Berlin, Washington DC Mall, and Quebec City data sets, respectively.
A Multivariate Framework for Variable Selection and Identification of Biomarkers in High-Dimensional Omics Data

In this thesis, we address the identification of biomarkers in highdimensional omics data. The identification of valid biomarkers is especially relevant for personalized medicine that depends on accurate prediction rules. Moreover, biomarkers elucidate the provenance of disease, or molecular changes related to disease. From a statistical point of view the identification of biomarkers is best cast as variable selection. In particular, we refer to variables as the molecular attributes under investigation, e.g. genes, genetic variation, or metabolites; and we refer to observations as the specific samples whose attributes we investigate, e.g. patients and controls. Variable selection in high-dimensional omics data is a complicated challenge due to the characteristic structure of omics data. For one, omics data is high-dimensional, comprising cellular information in unprecedented details. Moreover, there is an intricate correlation structure among the variables due to e.g internal cellular regulation, or external, latent factors. Variable selection for uncorrelated data is well established. In contrast, there is no consensus on how to approach variable selection under correlation. Here, we introduce a multivariate framework for variable selection that explicitly accounts for the correlation among markers. In particular, we present two novel quantities for variable importance: the correlation-adjusted t (CAT) score for classification, and the correlation-adjusted (marginal) correlation (CAR) score for regression. The CAT score is defined as the Mahalanobisdecorrelated t-score vector, and the CAR score as the Mahalanobis-decorrelated correlation between the predictor variables and the outcome. We derive the CAT and CAR score from a predictive point of view in linear discriminant analysis and regression; both quantities assess the weight of a decorrelated and standardized variable on the prediction rule. Furthermore, we discuss properties of both scores and relations to established quantities. Above all, the CAT score decomposes Hotelling’s T2 and the CAR score the proportion of variance explained. Notably, the decomposition of total variance into explained and unexplained variance in the linear model can be rewritten in terms of CAR scores. To render our approach applicable on high-dimensional omics data we devise an efficient algorithm for shrinkage estimates of the CAT and CAR score. Subsequently, we conduct extensive simulation studies to investigate the performance of our novel approaches in ranking and prediction under correlation. Here, CAT and CAR scores consistently improve over marginal approaches in terms of more true positives selected and a lower model error. Finally, we illustrate the application of CAT and CAR score on real omics data. In particular, we analyze genomics, transcriptomics, and metabolomics data. We ascertain that CAT and CAR score are competitive or outperform state of the art techniques in terms of true positives detected and prediction error.
An adaptive echo canceller using parallel Kalman filters

This paper presents a new method for an adaptive echo canceller in a long distance transmission channel. Since the number of parameters of an echo path is usually greater than 100, it is desired to estimate them as efficiently as possible for real-time processing. We propose new type filters, called parallel Kalman filters, based on the divided estimation of impulse response of an echo path. If the parallel Kalman filters are used, then the number of parameters to be estimated by one processor becomes much smaller than that by the usual Kalman filter. Since complete parallel computations are possible, this algorithm is suitable for an adaptive echo canceller operating in real time. It is very important that the convergency of the estimates to true parameters is guaranteed in the proposed echo canceller under some assumptions.
Glomerular Loss After Renal Radiofrequency Ablation Are Comparable to 30 Minutes of Warm Ischemia.

PURPOSE To compare, with stereological methods, the glomerular loss in kidneys submitted to radiofrequency ablation (RFA) or warm ischemia. MATERIALS AND METHODS Twenty-six male pigs were divided into three groups. Eight animals were allocated in the sham group, which was submitted to laparoscopic dissection of the left renal hilum, without renal ischemia. Eight animals were allocated in the ischemia group, which had the left renal hilum clamped for 30 minutes under laparoscopic access. Ten animals were submitted to RFA of the left kidney lower pole, under laparoscopic visualization. Animals were euthanized 21 days after surgery, when kidneys were collected. Fragments of the upper pole of the left kidney were processed for morphometric analysis. Right kidney was used as self-controls for each animal. Glomerular volumetric density (Vv[glom]); volume-weighted glomerular volume (VWGV); and glomerular density were quantified by stereological methods and compared by Student's t-test and one-way-analysis of variance with Dunnett's post-test. RESULTS Three animals in the RFA group developed postoperative complications (Urinoma/Hydronephrosis) and were excluded from the analysis. No difference was found among the kidneys submitted to RFA and warm ischemia for all parameters. However, these kidneys showed lower Vv[glom] and glomerular density when compared to its self-controls (right kidneys), and when compared to sham-operated animals (p < 0.05). No difference was observed in regards to VWGV among the groups. CONCLUSION RFA in pigs determines a significant reduction of glomerular density in the remaining parenchyma. This alteration was comparable to that observed in kidneys submitted to 30 minutes of warm ischemia.
Epidemiologie und Prophylaxe der Leptospirose beim Hund

Zusammenfassung Die Leptospirose ist eine Zoonose mit steigender Prävalenz bei Hunden und Menschen in Deutschland. Die verschiedenen Leptospiren-Serovare haben unterschiedliche Pathogenität. Auch gesunde infizierte Hunde scheiden Leptospiren über den Urin aus und stellen somit ein Infektionsrisiko für Menschen und andere Tiere dar. Die Impfung ist die wichtigste Maßnahme zum Schutz; sie verhindert nicht nur die Krankheit beim Hund, sondern vermindert auch die Ausscheidung von Leptospiren über den Urin. Für einen möglichst umfassenden Impfschutz sollten tetravalente Impfstoffe verwendet werden, die Serovare der in der Region relevanten Serogruppen enthalten. Die Verbreitung der Erreger kann durch die weite Anwendung dieser Impfstoffe reduziert werden. Eine ausführliche Besitzeraufklärung über das zoonotische Potenzial der Leptospirose und geeignete Hygienemaßnahmen beim Umgang mit infizierten Hunden und Hundeurin sind essenziell.
An Osteoblast Origin for Craniofacial Dysplasia in Neurofibromatosis Type I

Sphenoid wing dysplasia (SWD), which results in a craniofacial deformity, is the third most common skeletal deformity in Neurofibromatosis Type I (NF1) patients. A neurofibromin osteoblast conditional deletion mouse model (Nf1ob-/-) has been developed to study the skeletal abnormalities in NF1. No overt morphological phenotype is seen in the appendicular or axial skeleton of these mice. Nf1ob-/mice have been shown to have increased bone porosity and lower bone density. We noted a progressive craniofacial deformity, which results in cranial asymmetry, malocclusion and unilateral proptosis of an eye. To assess this deformity, we employed micro-computed tomography (μCT) and geometric morphometric analysis to compare Nf1ob-/-mouse skulls to control animals. Landmarks were placed on the images at 13 biologically relevant cranial anatomical sites. Analysis of distances and angles between these landmarks revealed that there is significant variation between the Nf1ob-/mice and controls. We found that the nasal and frontal bones of Nf1ob-/mice skulls are deviated from the central line, whereas it was straight in controls. The nasal region is tipped downward in Nf1ob-/mice. We also noted that the cranium shows a trend toward macrocephaly in Nf1ob-/mice whereas other measurements were within the range of normal control mice. These differences correspond to those seen in craniofacial dysplasia and SWD in NF1 patients. No tumors were found associated with the craniofacial dysplasia in Nf1ob-/mice. Our results identify a primarily osteoblast origin for the pathogenesis of craniofacial dysplasia in Nf1ob-/mice and strongly support an osteoblast origin for SWD in NF1. In addition, we identify and validate a novel mouse model with which to explore molecular mechanisms and test preventative treatments for SWD in NF1.
DSA and ECDSA-based Multi-Signature Schemes

Summary This paper presents two new multi-signature schemes which aim at providing data authenticity, integrity, and non-repudiation. The proposed signing/verifying schemes are extensions of standardized algorithms, such as DSA (Digital Signature Algorithm) and ECDSA (Elliptic Curve DSA) algorithms. These schemes are faster than repeated individual signature (RDSA) using DSA or ECDSA (RECDSA) to generate a multi-signature. The final multi-signature of a message can be verified individually for each signer or collectively for a subgroup or entire group as well. Moreover, these schemes can also be used for group membership authentication. Finally, the proposed schemes can be used in E-commerce and E-government application. The security of the proposed schemes corresponds to the security of DSA and ECDSA algorithms respectively.
Effect of Ursolic Acid on Metabolic Syndrome, Insulin Sensitivity, and Inflammation.

To evaluate the effect of ursolic acid on metabolic syndrome, insulin sensitivity, and inflammation, a randomized, double-blind, placebo-controlled clinical trial was carried out in 24 patients (30-60 years) with a diagnosis of metabolic syndrome without treatment. They were randomly assigned to two groups of 12 patients, each to receive orally 150 mg of ursolic acid or homologated placebo once a day for 12 weeks. Before and after the intervention, the components of metabolic syndrome, insulin sensitivity (Matsuda index), and inflammation profile (interleukin-6 and C-reactive protein) were evaluated. After ursolic acid administration, the remission of metabolic syndrome occurred in 50% of patients (P = .005) with significant differences in body weight (75.7 ± 11.5 vs. 71 ± 11 kg, P = .002), body mass index (BMI) (29.9 + 3.6 vs. 24.9 ± 1.2 kg/m2, P = .049), waist circumference (93 ± 8.9 vs. 83 + 8.6 cm, P = .008), fasting glucose (6.0 ± 0.5 vs. 4.7 ± 0.4 mmol/L, P = .002), and insulin sensitivity (3.1 ± 1.1 vs. 4.2 ± 1.2, P = .003). Ursolic acid administration leads to transient remission of metabolic syndrome, reducing body weight, BMI, waist circumference and fasting glucose, as well as increasing insulin sensitivity.
Conversations with independent young adult online language learners

English Discoveries Online (EDO) is an English Language Online Learning program that contains a plethora of online learning resources for beginner to advanced learners distributed over nine levels (EduSoft, n.d.). These resources allow learners to develop individual language skills through exploration, learning and practice at their own pace, and in a manner that suit their own learning styles, abilities and preferences. Integrated multi media such as text, sound, video, graphics and animation, are combined in a non-linear interactive way through hyper-linking. It allows numerous forms of interaction and collaboration such as email, instant messaging, chats, forums and notice boards (AuraTech, n.d.).
Postural Stability Induced by Supervised Physical Training may improve also Oxygen Cost of Exercise and Walking Capacity in Post-Menopause, Obese Women

We utilized the training impulses method to numerically quantify the volume of physical exercise to be prescribed to postmenopausal obese women in such a way of obtain the best possible improvement of their health-related quality of life. Nine women (57±4 years, 89±2 kg, 157±9 cm) carried out 3-months of exercise training (3 session/week each lasting 80 min) under the supervision of skilled operators which indirectly calculated the volume of physical exercise by assessing heart rate values while patient exercised and making sure that the workload corresponded to 50-60% of their maximum oxygen uptake. Before and after training anthropometric, functional and biomechanical variables were assessed. After training patients shoved statistically signifi cant (P<0.05) reduction in body mass (-2%) and body mass index (-4%), waist circumference (-4%), total (-6%) and LDL (-26%) serum cholesterol and glycaemia (-8%), diastolic arterial blood pressure (-14%), and oxygen cost (-14%) at the maximum workload during incremental cardiopulmonary test, the sway area from unipedal stance (right leg) of 20 s on a pressure platform (-49%), while increased both free fat body mass percentage (+3%) and space covered during the six minute walk test (+11%). It was concluded that, when an exercise protocol is carried out by postmenopausal obese women and the volume of exercise is instrumentally controlled by experienced operators, it could result in an effective benefi t on the quality of life of these patients since they ameliorate some critical anthropometric and functional parameters. Research Article Postural Stability Induced by Supervised Physical Training may improve also Oxygen Cost of Exercise and Walking Capacity in Post-Menopause, Obese Women Fernanda Velluzzi1, Massimiliano Pau2, Andrea Loviselli1, Raffaele Milia3, Daniela Lai1, Daniele Concu4, Gianmarco Angius4, Abdallah Raweh5, Andrea Fois6 and Alberto Concu3,4,5 1Obesity Centre, Medical Faculty of the University of Cagliari, Italy 2Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, Italy 3Sports Physiology Laboratory, Department of Medical Sciences, University of Cagliari, Italy 42C Technologies Ltd, Academic Spin-off, University of Cagliari, Italy 5Medical Sciences Faculty, the LUdeS Foundation Higher Education Institution, Malta 6EventFeel Ltd, Cagliari, Italy *Address for Correspondence: Alberto Concu, Sports Physiology Laboratory, Department of Medical Sciences, University of Cagliari, Italy, Tel: +393386239125; Email: aconcu44@gmail.com Submitted: 21 December 2016 Approved: 06 January 2017 Published: 09 January 2017 Copyright: 2017 Concu, et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.