Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative analysis of different techniques in classification based on association rules

Classification is a machine learning procedure that tags data instances into predefined class labels which are used to predict the data according to those Classes. Many classification algorithms in data mining have been stated, such as: C4.5, Apriori, Genetic algorithm, and Fuzzy set approaches which mainly uses heuristic or greedy search to get frequent sets in data for classification, resulting in high error ratio. Recently, a new method for classification has been proposed, called the Classification Using Association also known as associative classification. The main purpose for this is to mine class-association rules. Associative Classification has more advantages than the heuristic and greedy method, as it easily removes noise and higher accuracy is obtained. It additionally generates a rule set, that are more complete than traditional classification methods. This paper presents a meticulous survey on various Associative classification techniques. Moreover, a comparative analysis of accuracy and efficiency of those methods is presented.
Integrated transformer baluns for RF low noise and power amplifiers

On-chip transformer baluns integrated with an RF front-end architecture for medium power WLAN is presented. Method of measuring and characterizing a 3-port balun with a 2-port network analyzer is discussed. Implemented in 0.18mum CMOS, the receive path including a switch, an input transformer and a differential LNA, achieves S21 of 17dB, NF of 4.1dB, and IIP3 of 0dBm at 2.45GHz; the transmit path of a differential PA with an output transformer, achieves Psat of 21dBm, P1dB of 17dBm, and max PAE of 21%
Fused FDG-PET/contrast-enhanced CT detects occult subdiaphragmatic involvement of Hodgkin's lymphoma thereby identifying patients requiring six cycles of anthracycline-containing chemotherapy and consolidation radiation of spleen.

BACKGROUND Spleen and liver assessment for occult involvement of Hodgkin's lymphoma (HL) challenges current staging procedures. PATIENTS AND METHODS We prospectively evaluated event-free survival (EFS) in 103 HL patients staged with fused 2-[fluorine-18]fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/contrast-enhanced computed tomography (CT) to identify those at greatest risk for abdominal relapse. The EFS of this series was compared with that of a historical cohort of 100 HL patients staged with separate FDG-PET and diagnostic CT acquisitions. RESULTS Thirty-one of the 103 patients staged with FDG-PET/contrast-enhanced CT were found to have spleen involvement and 10 patients liver involvement, whereas 14 of the 100 patients staged with separate procedures were found to have spleen involvement and 3 patients liver involvement. There were significantly more intensive treatments (six courses of anthracycline-containing chemotherapy and spleen radiation) in the fused PET/CT group than in the historical cohort (P ≤ 0.04). At a median follow-up of 27 months, five events occurred in the fused PET/CT group (HL relapse, 4 patients; carcinoma, 1 patient) and 19 events in the historical cohort (HL relapse, 18 patients; acute promyelocytic leukemia, 1 patient). Ten of the 18 relapses in the historical cohort were localized in the spleen and/or liver area. None of the four relapses in the fused PET/CT group was localized below the diaphragm. Thus, FDG-PET/contrast-enhanced CT-guided treatment resulted in a 95% EFS, whereas separate FDG-PET and diagnostic CT-guided treatment resulted in an 81% EFS (P = 0.002). CONCLUSION FDG-PET/contrast-enhanced CT is an accurate frontline single imaging diagnostic tool enabling effective tailored treatment in HL patients.
The Combination of Cyst Fluid Carcinoembryonic Antigen, Cytology and Viscosity Increases the Diagnostic Accuracy of Mucinous Pancreatic Cysts

Background/Aims The objective of this study was to investigate the value of cyst fluid carcinoembryonic antigen (CEA) in combination with cytology and viscosity for the differential diagnosis of pancreatic cysts. Methods We retrospectively reviewed our data for patients who underwent endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) and cyst fluid analysis. We investigated the sensitivity, specificity and accuracy of the combination of cyst fluid CEA, cytology and viscosity testing. Results A total of 177 patients underwent EUS-FNA and cyst fluid analysis. Of these, 48 subjects were histologically and clinically confirmed to have pancreatic cysts and were therefore included in the analysis. Receiver operator curve analysis demonstrated that the optimal cutoff value of cyst fluid CEA for differentiating mucinous versus nonmucinous cystic lesions was 48.6 ng/mL. The accuracy of cyst fluid CEA (39/48, 81.3%) was greater than the accuracy of cytology (23/45, 51.1%) or the string sign (33/47, 70.2%). Cyst fluid CEA in combination with cytology and string sign assessment exhibited the highest accuracy (45/48, 93.8%). Conclusions Cyst fluid CEA was the most useful single test for identifying mucinous pancreatic cysts. The addition of cytology and string sign assessment to cyst fluid CEA increased the overall accuracy for the diagnosis of mucinous pancreatic cysts.
Record, Transform & Reproduce Social Encounters in Immersive VR: An Iterative Approach

Immersive Virtual Reality Environments that can be accessed through multimodal natural interfaces will bring new affordances to mediated interaction with virtual embodied agents and avatars. Such interfaces will measure, amongst others, users' poses and motion which can be copied to an embodied avatar representation of the user that is situated in a virtual or augmented reality space shared with autonomous virtual agents and human controlled or semi-autonomous avatars. Designers of such environments will be challenged to facilitate believable social interactions by creating agents or semi-autonomous avatars that can respond meaningfully to users' natural behaviors, as captured by these interfaces. In our future research, we aim to realize such interactions to create rich social encounters in immersive Virtual Reality. In this current work, we present the approach we envisage to analyze and learn agent behavior from human-agent interaction in an iterative fashion. We specifically look at small-scale, `regulative' nonverbal behaviors. Agents inform their behavior on previous observations, observing responses that these behaviors elicit in new users, thus iteratively generating corpora of short, situated human-agent interaction sequences that are to be analyzed, annotated and processed to generate socially intelligent agent behavior. Some choices and challenges of this approach are discussed.
eStor: Energy efficient and resilient data center storage

Much recent research work seeks to turn off servers and redirect I/O load for energy efficiency under low utilization period, but most of them are highly constrained by data layout policy. There are two widely used replica placement schemes. One is sequential data layout policy like in Chained Declustering, which allows to power down a large fraction of nodes without disrupting data availability, but has poor data rebuild parallelism to be resilient to node failure. Another is random data layout policy like in GFS and HDFS where its property is precisely opposite to that of the sequential policy. In this paper, we propose a hybrid data layout policy named eStor, which integrates the advantages of both sequential and random data layout policy. Under the eStor policy some replicas are placed in a sequential way, while other replicas are placed in a random fashion. It allows users to configure the system parameters of replication level and number of replicas placed in sequential way. By adjusting the system parameters, it can turn off a large amount of nodes without data loss and also has high data rebuild parallelism in case of failure. Experiments with eStor implemented in Hadoop demonstrate that it can mostly save 40% of the energy consumed and has high data rebuild rate.
Factorization for Probabilistic Local Appearance Models

We propose a novel local appearance modeling method for object detection and recognition in cluttered scenes. The approach is based on the joint distribution of local feature vectors at multiple salient points and factorization with Independent Component Analysis (ICA). The resulting non-parametric densities are simple multiplicative histograms. This leads to computationally tractable joint probability densities which can model high-order dependencies. Furthermore, we propose a distance-sensitive histograming technique for capturing spatial dependencies which are otherwise lost in the joint feature distributions. The advantages over existing techniques include the ability to model non-rigid objects and the flexibility in modeling spatial or structural relationships between object parts. Testing and evaluation shows that the factorized density model with spatial encoding improves modeling accuracy and outperforms global appearance models in image/object retrieval. Furthermore, experiments in detection of substantially occluded objects in cluttered scenes have demonstrated promising results.
Gender Differences and Similarities in Perceptions and Experiences of Secondary Public School Safety

Gender Differences and Similarities in Perceptions and Experiences of Secondary Public School Safety Bryan Kent Young Department of Counseling Psychology and Special Education Educational Specialist in School Psychology This study is a description of male and female secondary students’ experiences of safety in public schools. Gender differences in reported victimization and perceptions of school safety have been noted. The National Center for Educational Statistics ([NCES], 2006) reported that boys were the victims of violent acts in the schools more often than girls. Many studies have reported different results relating to how safe students perceive their schools to be (Addington et al., 2002; Office of Educational Research and Improvement, 1997). This study considered gender differences and similarities in students’ perceptions of school safety. The study utilized a qualitative research approach to describe students’ experiences. Focus groups composed of secondary public school students discussed their perceptions and experiences of school safety. The focus groups were divided into three categories: mixed genders, all male, and all female. The data were analyzed by gender to provide descriptions of what might contribute to students’ perceptions, experiences, and feelings in school. Students reported feelings of safety and danger in the schools from the following sources: peers, teachers and staff, and environmental context. Within these three categories the following themes were identified: (a) peers included friends, groups, and weapons; (b) teachers and staff included supervision and student-teacher relationships; and (c) environmental context included hallways and cameras/officers. Gender differences were noted in students’ comments describing their experiences related to safety in the schools. Boys reported looking toward teachers and peers for protection from physical harm. Girls reported using relationships with friends and school faculty members as a source of emotional security and comfort. Similarities across gender were noted in students’ perceptions regarding the need for extra security measures and the need for more trusting relationships with teachers and peers. Based on students’ comments and considering gender differences, the effectiveness of school safety measures may be increased if administration considered the needs of each gender.
Prediction and Characterization of Small Non-Coding RNAs Related to Secondary Metabolites in Saccharopolyspora erythraea

Saccharopolyspora erythraea produces a large number of secondary metabolites with biological activities, including erythromycin. Elucidation of the mechanisms through which the production of these secondary metabolites is regulated may help to identify new strategies for improved biosynthesis of erythromycin. In this paper, we describe the systematic prediction and analysis of small non-coding RNAs (sRNAs) in S. erythraea, with the aim to elucidate sRNA-mediated regulation of secondary metabolite biosynthesis. In silico and deep-sequencing technologies were applied to predict sRNAs in S. erythraea. Six hundred and forty-seven potential sRNA loci were identified, of which 382 cis-encoded antisense RNA are complementary to protein-coding regions and 265 predicted transcripts are located in intergenic regions. Six candidate sRNAs (sernc292, sernc293, sernc350, sernc351, sernc361, and sernc389) belong to four gene clusters (tpc3, pke, pks6, and nrps5) that are involved in secondary metabolite biosynthesis. Deep-sequencing data showed that the expression of all sRNAs in the strain HL3168 E3 (E3) was higher than that in NRRL23338 (M), except for sernc292 and sernc361 expression. The relative expression of six sRNAs in strain M and E3 were validated by qRT-PCR at three different time points (24, 48, and 72 h). The results showed that, at each time point, the transcription levels of sernc293, sernc350, sernc351, and sernc389 were higher in E3 than in M, with the largest difference observed at 72 h, whereas no signals for sernc292 and sernc361 were detected. sernc293, sernc350, sernc351, and sernc389 probably regulate iron transport, terpene metabolism, geosmin synthesis, and polyketide biosynthesis, respectively. The major significance of this study is the successful prediction and identification of sRNAs in genomic regions close to the secondary metabolism-related genes in S. erythraea. A better understanding of the sRNA-target interaction would help to elucidate the complete range of functions of sRNAs in S. erythraea, including sRNA-mediated regulation of erythromycin biosynthesis.
Named Entity Recognition for Nepali Text Using Support Vector Machines

Named Entity Recognition aims to identify and to classify rigid designators in text such as proper names, biological species, and temporal expressions into some predefined categories. There has been growing interest in this field of research since the early 1990s. Named Entity Recognition has a vital role in different fields of natural language processing such as Machine Translation, Information Extraction, Question Answering System and various other fields. In this paper, Named Entity Recognition for Nepali text, based on the Support Vector Machine (SVM) is presented which is one of machine learning approaches for the classification task. A set of features are extracted from training data set. Accuracy and efficiency of SVM classifier are analyzed in three different sizes of training data set. Recognition systems are tested with ten datasets for Nepali text. The strength of this work is the efficient feature extraction and the comprehensive recognition techniques. The Support Vector Machine based Named Entity Recognition is limited to use a certain set of features and it uses a small dictionary which affects its performance. The learning performance of recognition system is observed. It is found that system can learn well from the small set of training data and increase the rate of learning on the increment of training size.
Consistent and predictable delivery rates after oocyte vitrification: an observational longitudinal cohort multicentric study.

BACKGROUND An efficient method for cryopreservation of human oocytes may offer solutions to legal and ethical problems in routine infertility programs and may also be used for fertility preservation for medical and social reasons. METHODS We conducted an observational longitudinal cohort multicentric study to investigate the efficacy and reproducibility of oocyte cryopreservation outcomes in IVF/ICSI cycles. Moreover, the effects of patient and cycle characteristics on the delivery rate (DR) were analyzed. RESULTS In 486 cycles performed in 450 couples, 2721 oocytes were warmed and 2304 of them survived cryopreservation (84.7%). Of the 2182 oocytes subjected to ICSI, the rates of fertilization and development to top-quality embryos were 75.2 and 48.1%, respectively. A total of 128 deliveries were obtained (26.3% per cycle and 29.4% per transfer) for 450 patients (28.4%) and 147 babies were live born from 929 embryos transferred (15.8%). The forward logistic regression analysis on a per patient basis showed that female age [odds ratio (OR): 0.93, 95% confidence interval (CI): 0.88-0.98], number of vitrified oocytes (OR: 1.08, 95% CI: 1.01-1.17) and the day of transfer (OR: 1.97, 95% CI: 1.14-3.42) influenced DR. By recursive partitioning analysis, it can be estimated that more than eight oocytes vitrified are required to improve the outcome (22.6 versus 46.4% DR, respectively). When fewer oocytes are available in women aged >38 years, results are dramatically reduced (12.6 versus 27.5% DR, respectively). Conversely, when >8 oocytes are available, blastocyst culture represents the most efficient policy (62.1% DR; data from one center only). CONCLUSIONS Oocyte vitrification is an efficient and reliable approach, with consistent results between centers and predictable DRs. It should be applied routinely for various indications. A predictive model is proposed to help patient counselling and selection.
International Journal of Advanced Robotic Systems Inverse Kinematics of a New Quadruped Robot Control Method Regular Paper

Design of redudant joints has been widely used in quadruped robots, so new kinds of techniques for sloving inverse kinematics are needed. In this paper we propose a new control method called Time‐Pose control method and choose the enhanced extended jacobian matrix method for inverse kinematics. We deduce extended jacobian matrix method again so that it can be applicable for arbitrary joint length. It is argued that because the method can generate close joint angle path. With Time‐Pose control method, such kind of inverse kinematics method has been used for trot gait on the flat ground. Simulations and experiments are performed, which prove the extended jacobian matrix method to be realizable for the quadruped robot.
OSM1/SYP61: A Syntaxin Protein in Arabidopsis Controls Abscisic Acid–Mediated and Non-Abscisic Acid–Mediated Responses to Abiotic Stress

To identify the genetic loci that control salt tolerance in higher plants, a large-scale screen was conducted with a bialaphos marker–based T-DNA insertional collection of Arabidopsis ecotype C24 mutants. One line, osm1 (for osmotic stress–sensitive mutant), exhibited increased sensitivity to both ionic (NaCl) and nonionic (mannitol) osmotic stress in a root-bending assay. The osm1 mutant displayed a more branched root pattern with or without stress and was hypersensitive to inhibition by Na+, K+, and Li+ but not Cs+. Plants of the osm1 mutant also were more prone to wilting when grown with limited soil moisture compared with wild-type plants. The stomata of osm1 plants were insensitive to both ABA-induced closing and inhibition of opening compared with wild-type plants. The T-DNA insertion appeared in the first exon of an open reading frame on chromosome 1 (F3M18.7, which is the same as AtSYP61). This insertion mutation cosegregated closely with the osm1 phenotype and was the only functional T-DNA in the mutant genome. Expression of the OSM1 gene was disrupted in mutant plants, and abnormal transcripts accumulated. Gene complementation with the native gene from the wild-type genome completely restored the mutant phenotype to the wild type. Analysis of the deduced amino acid sequence of the affected gene revealed that OSM1 is related most closely to mammalian syntaxins 6 and 10, which are members of the SNARE superfamily of proteins required for vesicular/target membrane fusions. Expression of the OSM1 promoter::β-glucuronidase gene in transformants indicated that OSM1 is expressed in all tissues except hypocotyls and young leaves and is hyperexpressed in epidermal guard cells. Together, our results demonstrate important roles of OSM1/SYP61 in osmotic stress tolerance and in the ABA regulation of stomatal responses.
A Study of the Reionization History of Intergalactic Helium with FUSE and the Very Large Telescope

We obtained high-resolution Far Ultraviolet Spectroscopic Explorer (FUSE; R ~ 20,000) and Very Large Telescope (VLT; R ~ 45,000) spectra of the quasar HE 2347-4342 in order to study the properties of the intergalactic medium between redshifts z = 2.0 and 2.9. The high-quality optical spectrum allows us to identify approximately 850 H I absorption lines with column densities between N ~ 5 × 1011 and 1018 cm-2. The reprocessed FUSE spectrum extends the wavelength coverage of the He II absorption down to an observed wavelength of 920 Å. Source flux is detected to rest-frame wavelengths as short as ~237 Å. Approximately 1400 He II absorption lines are identified, including 917 He II Lyα systems and some of their He II Lyβ, Lyγ, and Lyδ counterparts. The ionization structure of He II is complex, with approximately 90 absorption lines that are not detected in the hydrogen spectrum. These features may represent the effect of soft ionizing sources. The ratio η = N(He )/N(H ) varies approximately from unity to more than a thousand, with a median value of 62 and a distribution consistent with the intrinsic spectral indexes of quasars. This provides evidence that the dominant ionizing field is from the accumulated quasar radiation, with contributions from other soft sources such as star-forming regions and obscured active galactic nuclei, which do not ionize helium. We find an evolution in η toward smaller values at lower redshift, with the gradual disappearance of soft components. At redshifts z > 2.7, the large but finite increase in the He II opacity, τ = 5 ± 1, suggests that we are viewing the end stages of a reionization process that began at an earlier epoch. Fits of the absorption profiles of unblended lines indicate comparable velocities between hydrogen and He+ ions. For line widths b = ξbH, we find ξ = 0.95 ± 0.12, indicating a velocity field in the intergalactic medium dominated by turbulence. At hydrogen column densities N < 3 × 1012 cm-2, the number of forest lines shows a significant deficit relative to a power law and becomes negligible below N = 1011 cm-2.
Capacity Analysis of MIMO Spatial Channel Model using Novel Adaptive Semi Blind Estimation Scheme

Multiple Input Multiple Output (MIMO) has been remained in much importance in recent past because of high capacity gain over a single antenna system. In this article, analysis over the capacity of the MIMO channel systems with spatial channel has been considered when the channel state information (CSI) is considered imperfect or partial. The dynamic CSI model has also been tried consisting of channel mean and covariance which leads to extracting of the channel estimates and error covariance. Both parameters indicated the CSI quality since these are the functions of temporal correlation factor, and based on this, the model covers data from perfect to statistical CSI, either partial or full blind. It is found that in case of partial and imperfect CSI, the capacity depends on the statistical properties of the error in the CSI. Based on the knowledge of statistical distribution of the deviations in CSI knowledge, a new estimation approach which maximizes the capacity of spatial channel model has been tried. The interference interactively reduced by employing the iterative channel estimation and data detection approach.
Detection of similarities in student programs: YAP'ing may be preferable to plague'ing

It has argued that systems for detecting similarities in submitted programs must be based on the analysis of program structure. One such system is “Plague”. In this paper, some difficulties with the Plague system are outlined and a new system is described that achieves the same goals as Plague, but in a way that is both more portable and more easily customized to new target languages.