Miracle-dz/UniFAR-FTUs huggingface dataset:
Forecasting using Artificial Neural Network and Statistics Models

Forecasting is very important for planning and decision-making in all fields to predict the conditions and cases surrounding the problem under study before making any decision. Hence, many forecasting methods have been developed to produce accurate predicted values. Consumer price indices provide appropriate and timely information about prices changes, which affect the economy of all Yemenis because of their different uses in many ways. It can be used as an economic indicator (wider use in the inflation measurement), and as a means of regulating income. It is also used as a supplement for statistical chains to predict future value indices in order to make sure that the data accurately reflect the patterns purchased by the Yemeni consumer. In this paper, we propose a modified artificial neural network method to predict the indices of consumer in the Republic of Yemen to the prices of the period from 01/01/2005 till 01/01/2014. The results of using the proposed method is compared to a classical statistical method. The proposed method is based on artificial neural networks, namely, back propagation with adaptive slope and momentum parameter to update weights. However, the statistical method is Box-Jenkins model which is used to predict time series. The experimental results show that artificial neural networks gives better predictive values due to their ability to deal with the nonlinear and stochastic data better than traditional statistical modeling techniques.
Highly Conserved Non-Coding Sequences and the 18q Critical Region for Short Stature: A Common Mechanism of Disease?

Background Isolated growth hormone deficiency (IGHD) and multiple pituitary hormone deficiency (MPHD) are heterogeneous disorders with several different etiologies and they are responsible for most cases of short stature. Mutations in different genes have been identified but still many patients did not present mutations in any of the known genes. Chromosomal rearrangements may also be involved in short stature and, among others, deletions of 18q23 defined a critical region for the disorder. No gene was yet identified. Methodology/Principal Findings We now report a balanced translocation X;18 in a patient presenting a breakpoint in 18q23 that was surprisingly mapped about 500 Kb distal from the short stature critical region. It separated from the flanking SALL3 gene a region enriched in highly conserved non-coding elements (HCNE) that appeared to be regulatory sequences, active as enhancers or silencers during embryonic development. Conclusion We propose that, during pituitary development, the 18q rearrangement may alter expression of 18q genes or of X chromosome genes that are translocated next to the HCNEs. Alteration of expression of developmentally regulated genes by translocation of HCNEs may represent a common mechanism for disorders associated to isolated chromosomal rearrangements.
Drug-Associated Adverse Events and Their Relationship with Outcomes in Patients Receiving Treatment for Extensively Drug-Resistant Tuberculosis in South Africa

Background Treatment-related outcomes in patients with extensively drug-resistant tuberculosis (XDR-TB) are poor. However, data about the type, frequency and severity of presumed drug-associated adverse events (AEs) and their association with treatment-related outcomes in patients with XDR-TB are scarce. Methods Case records of 115 South-African XDR-TB patients were retrospectively reviewed by a trained researcher. AEs were estimated and graded according to severity [grade 0 = none; grade 1–2 = mild to moderate; and grade 3–5 = severe (drug stopped, life-threatening or death)]. Findings 161 AEs were experienced by 67/115(58%) patients: 23/67(34%) required modification of treatment, the offending drug was discontinued in 19/67(28%), reactions were life-threatening in 2/67(3.0%), and 6/67(9.0%) died. ∼50% of the patients were still on treatment at the time of data capture. Sputum culture-conversion was less likely in those with severe (grade 3–5) vs. grade 0–2 AEs [2/27(7%) vs. 24/88(27%); p = 0.02]. The type, frequency and severity of AEs was similar in HIV-infected and uninfected patients. Capreomycin, which was empirically administered in most cases, was withdrawn in 14/104(14%) patients, implicated in (14/34) 41% of the total drug withdrawals, and was associated with all 6 deaths in the severe AE group (renal failure in five patients and hypokalemia in one patient). Conclusion Drug-associated AEs occur commonly with XDR-TB treatment, are often severe, frequently interrupt therapy, and negatively impact on culture conversion outcomes. These preliminary data inform on the need for standardised strategies (including pre-treatment counselling, early detection, monitoring, and follow-up) and less toxic drugs to optimally manage patients with XDR-TB.
Self-Rated Health Among Very Old People in European Countries

Objectives: To explore and gain insight into factors related to self-rated health (SRH) among very old people in two European countries. Methods: The study was based on Latvian (n = 301) and Swedish (n = 397) data from the baseline of the Enabling Autonomy, Participation, and Well-Being in Old Age: The Home Environment as a Determinant for Healthy Ageing Survey Study. Besides descriptive statistics, ordinal regression analysis was used to analyze demographic, physical and mental health-related, functional and environmental factors related to SRH in each sample. Results: In both samples, participants with worse perceived physical mobility and more symptoms were significantly more likely to have worse SRH. There were more diverse results regarding other factors in terms of opposite relations to SRH, comparing the two samples. Discussion: Preventive measures and health care should focus on improving and supporting mobility and physical health among older people. Especially in countries with low scores on indicators of health such as Latvia, to minimize health inequalities. More attention should be paid to factors to improve the general health status of the population.
Stadtpilot: Driving autonomously on Braunschweig's inner ring road

The development of the autonomous vehicle named “Caroline” for the 2007 DARPA Urban Challenge was a great opportunity to demonstrate the abilities of the Technische Universität Braunschweig in the research field of autonomous driving. Among 11 teams out of the initially 89, the CarOLO team mastered the challenges to qualify for the final DARPA Urban Challenge event. Based on this experience, the Technische Universität Braunschweig is currently working on the follow-up project “Stadtpilot” with the objective to drive fully autonomously on Braunschweig's entire ring road, which is known as the arterial road of its inner city traffic. This paper introduces the “Stadtpilot”-Project in the context of the Urban Challenge experience and identifies the differences to previous activities in this research context. The scientific claim will be shown in contrast to the Urban Challenge scenario. Completely new concepts are required to master the challenges of realizing autonomous driving in the domain of Braunschweig's inner ring road. An approach for the comprehensive treatment of path-planned sections is shown that realizes complex and precise autonomous driving maneuvers in a real urban environment and is observed as the first major success of the “Stadtpilot”-Project. Curvature optimized trajectories are generated over the whole roadway that are independent from the way driving decisions are found.
Binary codes K-modes clustering for HSI segmentation

An new pixel unsupervised hyperspectral image (HSI) segmentation method is proposed. It relies on a binary incoding of spectral reflectance curve variations of pixels that allows to consider HSI segmentation as a clustering problem in the feature set of binary strings. Using a generalized Hamming distance, a k-modes algorithm is applied to obtain a cluster partionning of the HSI with no use of any spatial information.
Variations of Antioxidant Characteristics and Mineral Contents in Pulp and Peel of Different Apple (Malus domestica Borkh.) Cultivars from Pakistan

Variations of phenolics, antioxidant activity, and mineral contents in peel and pulp of five apple (Malus domestica Borkh.) cultivars from Pakistan, namely Red Delicious, Golden Delicious, Kashmiri Amri, Kala Kulu and Sky Spur were appraised. The mean extract yield of antioxidant components obtained with 80:20 methanol-water (v/v), was found to be 22.1 g/100 g for peel and 14.2 g/100 g for pulp on a dry weight basis. The amounts of total phenolics and total flavonoids in peel and pulp of different cultivars of apple ranged from 1,907.5–2,587.9 mg gallic acid equivalent/100 g DW and 1,214.3–1,816.4 mg catechin equivalent/100 g DW and 1,185.2–1,475.5 mg GAE/100 g DW and 711.8–999.3 mg CE/100 g DW, respectively. The inhibition of linoleic acid peroxidation and DPPH scavenging activity of the extracts varied from 71.7–84.9 and 66.6–80.8% in peel, and 43.9–52.8 and 42.9–51.1% in pulp, respectively. Reducing power of the tested fruit part extracts at concentration 12.5 mg/mL ranged from 2.54–2.89 and 1.37–1.73, respectively. With regard to minerals analysis, both fruit parts showed the amount of K to be the highest, followed by Mg, Ca, Fe, Na and Zn. The results revealed that peel of the tested apple cultivars in this study had superior antioxidant capacity and mineral concentration than the pulp, indicating significant variations between the parts tested. Thus, consumption of apple fruits along with peel might be recommended to gaining better nutritive benefits.
A synchronization method for wireless acquisition systems, application to brain computer interfaces

A synchronization method for wireless acquisition systems has been developed and implemented on a wireless ECoG recording implant and on a wireless EEG recording helmet. The presented algorithm and hardware implementation allow the precise synchronization of several data streams from several sensor nodes for applications where timing is critical like in event-related potential (ERP) studies. The proposed method has been successfully applied to obtain visual evoked potentials and compared with a reference biosignal amplifier. The control over the exact sampling frequency allows reducing synchronization errors that will otherwise accumulate during a recording. The method is scalable to several sensor nodes communicating with a shared base station.
Socializing, networking and development: a report from the second ‘Young Microbiologists Symposium on Microbe Signalling, Organization and Pathogenesis’

In mid‐June, the second Young Microbiologists Symposium took place under the broad title of ‘Microbe signalling, organization and pathogenesis’ on the picturesque campus of University College Cork, Ireland. The symposium attracted 150 microbiologists from 15 different countries. The key feature of this meeting was that it was specifically aimed at providing a platform for junior scientists to present their work to a broad audience. The meeting was principally supported by Science Foundation Ireland with further backing from the Society for General Microbiology, the American Society for Microbiology and the European Molecular Biology Organization. Sessions focused on microbial gene expression, biogenesis, pathogenicity and host interaction. In this MicroMeeting report, we highlight some of the most significant advances and exciting developments reported during various talks and poster presentations given by the young and talented microbiologists.
Locus‐specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes

Locus‐specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer‐related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play an important role in disseminating clinical classification of variants. The IARC Working Group on Unclassified Genetic Variants has proposed a new system of five classes of variants in cancer susceptibility genes. However, standards are lacking for reporting and analyzing the multiple data types that assist in classifying variants. By adhering to standards of transparency and consistency in the curation and annotation of data, LSDBs can be critical for organizing our understanding of how genetic variation relates to disease. In this article we discuss how LSDBs can accomplish these goals, using existing databases for BRCA1, BRCA2, MSH2, MLH1, TP53, and CDKN2A to illustrate the progress and remaining challenges in this field. We recommend that: 1) LSDBs should only report a conclusion related to pathogenicity if a consensus has been reached by an expert panel. 2) The system used to classify variants should be standardized. The Working Group encourages use of the five class system described in this issue by Plon and colleagues. 3) Evidence that supports a conclusion should be reported in the database, including sources and criteria used for assignment. 4) Variants should only be classified as pathogenic if more than one type of evidence has been considered. 5) All instances of all variants should be recorded. Hum Mutat 29(11), 1273–1281, 2008. Published 2008 Wiley‐Liss, Inc.
Veto-based Malware Detection

Malicious software (malware) represents a threat to the security and privacy of computer users. Traditional signature-based and heuristic-based methods are unsuccessful in detecting some forms of malware. This paper presents a malware detection approach based on supervised learning. The main contributions of the paper are an ensemble learning algorithm, two pre-processing techniques, and an empirical evaluation of the proposed algorithm. Sequences of operational codes are extracted as features from malware and benign files. These sequences are used to produce three different data sets with different configurations. A set of learning algorithms is evaluated on the data sets and the predictions are combined by the ensemble algorithm. The predicted output is decided on the basis of veto voting. The experimental results show that the approach can accurately detect both novel and known malware instances with higher recall in comparison to majority voting.
Isolation of Paenibacillus illinoisensis That Produces Cyclodextrin Glucanotransferase Resistant to Organic Solvents

A bacterium that secreted cyclodextrin glucanotransferase (CGTase) in a medium overlaid with n-hexane was isolated and identified as Paenibacillus illinoisensis strain ST-12 K. The CGTase of the strain was purified from the culture supernatant. The molecular mass was 70 kDa. The enzyme was stable at pH 6 to 10 and active at pH 5.0 to 8.0. The optimum temperature at pH 7.0 was 65°C in the presence of 5 mM CaCl2. The enzyme produced mainly β-cyclodextrin. The total yield of α-, β-, and γ- cyclodextrins was increased 1.4-fold by the addition of ethanol. In particular, the yield of β-cyclodextrins in the presence of 10% (vol/vol) ethanol was 1.6-fold that without ethanol. The CGTase was stable and active in the presence of large amounts of various organic solvents.
Can we Evaluate the Quality of Generated Text?

Evaluating the output of NLG systems is notoriously difficult, and performing assessments of text quality even more so. A range of automated and subject-based approaches to the evaluation of text quality have been taken, including comparison with a putative gold standard text, analysis of specific linguistic features of the output, expert review and task-based evaluation. In this paper we present the results of a variety of such approaches in the context of a case study application. We discuss the problems encountered in the implementation of each approach in the context of the literature, and propose that a test based on the Turing test for machine intelligence offers a way forward in the evaluation of the subjective notion of text quality.
New Experimental Models of Diabetic Nephropathy in Mice Models of Type 2 Diabetes: Efforts to Replicate Human Nephropathy

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. The use of experimental models of DN has provided valuable information regarding many aspects of DN, including pathophysiology, progression, implicated genes, and new therapeutic strategies. A large number of mouse models of diabetes have been identified and their kidney disease was characterized to various degrees. Most experimental models of type 2 DN are helpful in studying early stages of DN, but these models have not been able to reproduce the characteristic features of more advanced DN in humans such as nodules in the glomerular tuft or glomerulosclerosis. The generation of new experimental models of DN created by crossing, knockdown, or knockin of genes continues to provide improved tools for studying DN. These models provide an opportunity to search for new mechanisms involving the development of DN, but their shortcomings should be recognized as well. Moreover, it is important to recognize that the genetic background has a substantial effect on the susceptibility to diabetes and kidney disease development in the various models of diabetes.
Crossing the Structure Chasm

It has frequently been observed that most of the world’s data lies outside database systems. The reason is that database systems focus on structured data, leaving the unstructured realm to others. The world of unstructured data has several very appealing properties, such as ease of authoring, querying and data sharing. In contrast, authoring, querying and sharing structured data require significant effort, albeit with the benefit of rich query languages and exact answers. We argue that in order to broaden the use of data management tools, we need a concerted effort to cross this structure chasm, by importing the attractive properties of the unstructured world into the structured one. As an initial effort in this direction, we introduce the REVERE System, which offers several mechanisms for crossing the structure chasm, and considers as its first application the chasm on the WWW. REVERE includes three innovations: (1) a data creation environment that entices people to structure data and enables them to do it rapidly; (2) a data sharing environment, based on a peer data management system, in which a web of data is created by establishing local mappings between schemas, and query answering is done over the transitive closure of these mappings; (3) a novel set of tools that are based on computing statistics over corpora of schemata and structured data. In a sense, we are trying to adapt the key techniques of the unstructured world, namely computing statistics over text coropra, into the world of structured data. We sketch how statistics computed over such corpora, which capture common term usage patterns, can be used to create tools for assisting in schema and mapping development. The initial application of REVERE focuses on creating a web of structured data from data that is usually stored in HTML web pages (e.g., personal information, course information,
The anatomy of prices on the French fish market

Hedonic price regressions have become a standard tool to study how prices of commodity goods are related to quality attributes. In this paper, we extend the traditional price specification by incorporating three sources of unobserved heterogeneity related to sellers, buyers, and matches between buyers and sellers. The extended price specification is estimated on a unique exhaustive dataset of nearly 15 million transactions occurring in French wholesale fish markets from 2002 to 2007. Results show that unobserved heterogeneity plays a significant role in price formation. For some species, its inclusion in price regressions changes the coefficients of quality-related fish characteristics. Last, using data analysis techniques, we classify fish and crustacean species by the extent to which price variations are related to fish characteristics, time effects and the three sources of unobserved heterogeneity.
Learning a Stopping Criterion for Active Learning for Word Sense Disambiguation and Text Classification

In this paper, we address the problem of knowing when to stop the process of active learning. We propose a new statistical learning approach, called minimum expected error strategy, to defining a stopping criterion through estimation of the classifier’s expected error on future unlabeled examples in the active learning process. In experiments on active learning for word sense disambiguation and text classification tasks, experimental results show that the new proposed stopping criterion can reduce approximately 50% human labeling costs in word sense disambiguation with degradation of 0.5% average accuracy, and approximately 90% costs in text classification with degradation of 2% average accuracy.
R5 Clade C SHIV Strains with Tier 1 or 2 Neutralization Sensitivity: Tools to Dissect Env Evolution and to Develop AIDS Vaccines in Primate Models

Background HIV-1 clade C (HIV-C) predominates worldwide, and anti-HIV-C vaccines are urgently needed. Neutralizing antibody (nAb) responses are considered important but have proved difficult to elicit. Although some current immunogens elicit antibodies that neutralize highly neutralization-sensitive (tier 1) HIV strains, most circulating HIVs exhibiting a less sensitive (tier 2) phenotype are not neutralized. Thus, both tier 1 and 2 viruses are needed for vaccine discovery in nonhuman primate models. Methodology/Principal Findings We constructed a tier 1 simian-human immunodeficiency virus, SHIV-1157ipEL, by inserting an “early,” recently transmitted HIV-C env into the SHIV-1157ipd3N4 backbone [1] encoding a “late” form of the same env, which had evolved in a SHIV-infected rhesus monkey (RM) with AIDS. SHIV-1157ipEL was rapidly passaged to yield SHIV-1157ipEL-p, which remained exclusively R5-tropic and had a tier 1 phenotype, in contrast to “late” SHIV-1157ipd3N4 (tier 2). After 5 weekly low-dose intrarectal exposures, SHIV-1157ipEL-p systemically infected 16 out of 17 RM with high peak viral RNA loads and depleted gut CD4+ T cells. SHIV-1157ipEL-p and SHIV-1157ipd3N4 env genes diverge mostly in V1/V2. Molecular modeling revealed a possible mechanism for the increased neutralization resistance of SHIV-1157ipd3N4 Env: V2 loops hindering access to the CD4 binding site, shown experimentally with nAb b12. Similar mutations have been linked to decreased neutralization sensitivity in HIV-C strains isolated from humans over time, indicating parallel HIV-C Env evolution in humans and RM. Conclusions/Significance SHIV-1157ipEL-p, the first tier 1 R5 clade C SHIV, and SHIV-1157ipd3N4, its tier 2 counterpart, represent biologically relevant tools for anti-HIV-C vaccine development in primates.
Spline-backfitted kernel smoothing of nonlinear additive autoregression model

Application of nonparametric and semiparametric regression techniques to high-dimensional time series data has been hampered due to the lack of effective tools to address the “curse of dimensionality. ” Under rather weak conditions, we propose spline-backfitted kernel estimators of the component functions for the nonlinear additive time series data that are both computationally expedient so they are usable for analyzing very high-dimensional time series, and theoretically reliable so inference can be made on the component functions with confidence. Simulation experiments have provided strong evidence that corroborates the asymptotic theory.
Complete Genome Sequence of Lactobacillus plantarum 10CH, a Potential Probiotic Lactic Acid Bacterium with Potent Antimicrobial Activity

ABSTRACT Lactobacillus plantarum 10CH is a bacteriocin-producing potential probiotic lactic acid bacterium (LAB) strain isolated from cheese. Its complete nucleotide sequence shows a single circular chromosome of 3.3 Mb, with a G+C content of 44.51%, a 25-gene plantaricin bacteriocin gene cluster, and the absence of recognized virulence factors.