Miracle-dz/UniFAR-FTUs huggingface dataset:
Survey of Human Group C Rotaviruses in Japan during the Winter of 1992 to 1993

ABSTRACT Fecal specimens from patients with acute diarrhea were collected from 10 prefectures in Japan over a 6-month period (November 1992 to April 1993), and the specimens that were negative for human group A rotaviruses were screened for the presence of human group C rotaviruses (CHRVs) by the reverse passive hemagglutination test. Of 784 specimens examined, 53 samples (6.8%) that were collected in 7 of 10 prefectures were positive for CHRV, indicating that CHRVs are widely distributed across Japan. Most of the CHRV isolates were detected in March and April, and CHRVs mainly prevailed in children ages 3 to 8 years. The genome electropherotypes of eight strains isolated in five individual prefectures were surprisingly similar to each other and were different from those of CHRV strains isolated to date. The outer capsid glycoprotein (VP7) gene homologies of the isolates retrieved in 1993 were subsequently analyzed by the dot blot hybridization method. As a result, the VP7 genes of the isolates revealed very high levels of homology not only with each other but also with the VP7 gene of the OK118 strain isolated in 1988. These results suggest that a large-scale outbreak of CHRV occurred during the winter of 1992 and 1993 in Japan.
Diagnosis of open-circuit faults in matrix converters

This paper presents a new diagnostic technique, known as the Modulated Error Voltages (MEV), for the diagnosis of open-circuits faults in the power switches of matrix converters. The proposed technique is based on the monitoring of nine modulated output error voltages, each one associated to a bidirectional switch of the converter. For each output phase, an error voltage is calculated and subsequently modulated by the gate signals of each one of the three bidirectional switches connected to that specific phase. Each modulated signal is subsequently averaged over a certain period of time. If at the end of this averaging period the obtained value is higher than a threshold limit, it will trigger the indication of an open-circuit fault in the power switch associated to the monitored signal. By using the MEV it is possible to concurrently detect and locate open-circuit faults, independently of the type of load of the matrix converter or its operating conditions, namely amplitude and frequency of the output voltages, both in steady-state and transient regimes. Moreover, the MEV allows to speed up the diagnostic process when compared to other diagnostic techniques, and can easily deal with the presence of multiple faults occurring simultaneously.
Treatment Outcome of Patients with Buruli Ulcer Disease in Togo

Background Following introduction of antimycobacterial treatment of Buruli ulcer disease (BUD), several clinical studies evaluated treatment outcomes of BUD patients, in particular healing times, secondary lesions and functional limitations. Whereas recurrences were rarely observed, paradoxical reactions and functional limitations frequently occurred. Although systematic BUD control in Togo was established as early as 2007, treatment outcome has not been reviewed to date. Therefore, a pilot project on post-treatment follow-up of BUD patients in Togo aimed to evaluate treatment outcomes and to provide recommendations for optimization of treatment success. Methodology/Principal Findings Out of 199 laboratory confirmed BUD patients, 129 could be enrolled in the study. The lesions of 109 patients (84.5%) were completely healed without any complications, 5 patients (3.9%) had secondary lesions and 15 patients (11.6%) had functional limitations. Edema, category III ulcers >15cm, healing times >180 days and a limitation of movement at time of discharge constituted the main risk factors significantly associated with BUD related functional limitations (P<0.01). Review of all BUD related documentation revealed major shortcomings, in particular concerning medical records on adjuvant surgical and physiotherapeutic treatment. Conclusions/Significance This study presents the first systematic analysis of treatment outcome of BUD patients from Togo. Median times to healing and the absence of recurrences were in line with findings reported by other investigators. The percentage of functional limitations of 11.6% was lower than in other studies, and edema, category III ulcers, healing time >180 days and limitation of movement at discharge constituted the main risk factors for functional limitations in Togolese BUD patients. Standardized treatment plans, patient assessment and follow-up, as well as improved management of medical records are recommended to allow for intensified monitoring of disease progression and healing process, to facilitate implementation of therapeutic measures and to optimize treatment success.
Differential Roles for Cyclin-Dependent Kinase Inhibitors p21 and p16 in the Mechanisms of Senescence and Differentiation in Human Fibroblasts

ABSTRACT The irreversible G1 arrest in senescent human diploid fibroblasts is probably caused by inactivation of the G1cyclin–cyclin-dependent kinase (Cdk) complexes responsible for phosphorylation of the retinoblastoma protein (pRb). We show that the Cdk inhibitor p21Sdi1,Cip1,Waf1, which accumulates progressively in aging cells, binds to and inactivates all cyclin E-Cdk2 complexes in senescent cells, whereas in young cells only p21-free Cdk2 complexes are active. Furthermore, the senescent-cell-cycle arrest occurs prior to the accumulation of the Cdk4-Cdk6 inhibitor p16Ink4a, suggesting that p21 may be sufficient for this event. Accordingly, cyclin D1-associated phosphorylation of pRb at Ser-780 is lacking even in newly senescent fibroblasts that have a low amount of p16. Instead, the cyclin D1-Cdk4 and cyclin D1-Cdk6 complexes in these cells are associated with an increased amount of p21, suggesting that p21 may be responsible for inactivation of both cyclin E- and cyclin D1-associated kinase activity at the early stage of senescence. Moreover, even in the late stage of senescence when p16 is high, cyclin D1-Cdk4 complexes are persistent, albeit reduced by ≤50% compared to young cells. We also provide new evidence that p21 may play a role in inactivation of the DNA replication factor proliferating cell nuclear antigen during early senescence. Finally, because p16 accumulates in parallel with the increases in senescence-associated β-Gal activity and cell volume that characterize the senescent phenotype, we suggest that p16 upregulation may be part of a differentiation program that is turned on in senescent cells. Since p21 decreases after senescence is achieved, this upregulation of p16 may be essential for maintenance of the senescent-cell-cycle arrest.
Generic text summarization using relevance measure and latent semantic analysis

In this paper, we propose two generic text summarization methods that create text summaries by ranking and extracting sentences from the original documents. The first method uses standard IR methods to rank sentence relevances, while the second method uses the latent semantic analysis technique to identify semantically important sentences, for summary creations. Both methods strive to select sentences that are highly ranked and different from each other. This is an attempt to create a summary with a wider coverage of the document's main content and less redundancy. Performance evaluations on the two summarization methods are conducted by comparing their summarization outputs with the manual summaries generated by three independent human evaluators. The evaluations also study the influence of different VSM weighting schemes on the text summarization performances. Finally, the causes of the large disparities in the evaluators' manual summarization results are investigated, and discussions on human text summarization patterns are presented.
Digital Commons @ Michigan Tech Digital Commons @ Michigan Tech Evaluation of artificial intelligence based models for chemical Evaluation of artificial intelligence based models for chemical biodegradability prediction biodegradability prediction

: This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.
BaLAnce: Battery Lifetime-Aware LTE Switching-Off Strategy in Green Network Infrastructures

The load-aware operation of network infrastructure is a well established green networking concept to improve the energy-efficiency of wireless communication networks. But while it has been shown that switching-off base stations in times of low traffic leads to significant savings of energy, the interdependency of such infrastructure-oriented measures on the power consumption of user equipments has not been addressed in detail so far. This paper therefore quantizes the negative impact of switching-off strategies for base stations on the battery lifetime of Long Term Evolution (LTE) devices. Therefore, the Context- Aware Power Consumption Model for LTE devices (CoPoMo) that enables an accurate quantification of the energy efficiency of devices under different network deployments, is leveraged. In order to enable a trade-off between energy savings in the infrastructure and battery lifetimes of devices on the user side, we propose a Battery-Lifetime-Aware switching-off Strategy (BaLAnce) for base stations. The results of a simulation study with a reference LTE network scenario show, that a significantly better energy trade-off can be achieved by BaLAnce.
Allometric growth coefficients and partitioning of fat depots in indigenous Ethiopian Menz and Horro sheep breds

A total of 146 Menz and Horro lambs of both sexes were serially slaughtered and dissected at 5 different stages of growth (i.e. at 1, 3, 6, 9 and 12 months of age) to define the pattern of growth and partitioning of fat among body depots of indigenous Ethiopian Menz and Horro sheep breeds. The GLM procedure of SAS and an allometric growth equation were used to assess the effects of various factors on the growth of body depots and to estimate rates of growth relative to Total Body Fat (TBF) and Empty Body Weight (EBW), respectively. Results obtained showed that the growth of carcass fat (CF), Non-Carcass Fat (NCF) and Tail Fat (TF) are significantly affected by the genotype (P<0.0001) and stage of growth (P<0.0001) of lambs. Except for CF growth of both NCF and TF were also significantly affected (P<0.001 and P<0.05, respectively) by the sex of the lamb and the season in which lambs were born. Menz sheep deposited more fat into CF and less in NCF depots as compared with Horro sheep. Females of both breeds tended to deposit more fat intra-abdominally than male lambs. In both breeds, the highest allometric growth coefficient obtained for TF and the lowest for NCF indicate that the former is a late developing while the later is an early maturing depot fat.
A building block approach to sensornet systems

We present a building block approach to hardware platform design based on a decade of collective experience in this area, arriving at an architecture in which general-purpose modules that require expertise to de sign and incorporate commonly-used functionality are integrated with application-specific carriers that satisfy the unique sensing, power supply, and mechanical constraints of an application. Of course, modules are widespread, but our focus is far less on the performance of any individual module and far more on an overall architecture that supports the prototype, pilot, and production stages of design, and preserves the artifacts and learnings accumulated along the way. We present heuristics for partitioning functionality between modules and carriers, and identify guidelines for their interconnection. Our approach advocates exporting a wide electrical interface, eliminating the system bus, and supporting many physical interconnect options for modules and carriers. We evaluate this approach by constructing a family of general-purpose modules and application-specific carriers that achieve a high degree of reuse despite very different application requirements. We show that this approach shortens platform development time-to-result for novice graduate students, making custom platforms broadly accessible.
Accuracy Evaluation of Deep belief Networks with Fixed-Point Arithmetic

Deep Belief Networks (DBNs) are state-of-art Machine Learning techniques and one of the most important unsupervised learning algorithms. Training DBNs is computationally intensive which naturally leads to investigate FPGA acceleration. Fixed-point arithmetic can be used when implementing DBNs in FPGAs to reduce execution time, but it is not clear the implications for accuracy. Previous studies have focused only on accelerators using some fixed bit-widths. A contribution of this paper is to demonstrate the bit-width effect on various configurations of DBNs in a comprehensive way by experimental evaluation. Explicit performance changing points are found using various bit-widths. The impact of sigmoid function approximation, required part of DBNs, is evaluated. A solution of mixed bit-widths DBN is proposed, fitting the bit-widths of FPGA primitives and gaining similar performance to the software implementation. Our results provide a guide to inform the design choices on bit-widths when implementing DBNs in FPGAs documenting clearly the trade-off in accuracy.
The effectiveness of deep brain stimulation in improving upper and lower extremity function under dual task conditions in Parkinson?’s disease patients

Parkinson? ’s disease (PD) is a progressive neurodegenerative disorder characterized by reduced movement. Postural instability and gait dysfunction (PIGD) is one of the more debilitating symptoms of PD due to its effect on activities of daily life and increased risk for falls. In later stages of the disease, cognitive impairment affects executive functioning and working memory. Although, most activities in daily living require both motor and cognitive functioning like cycling (motor) while holding a conversation (cognitive). Bilateral deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been shown to reduce motor deficits in advanced Parkinson? ’s disease patients. However, the effectiveness of STN DBS on postural instability is less pronounced. It has been shown that bilateral STN DBS results in cognitive declines under dual-? task conditions using an upper extremity task and these declines compromise motor function. The aim of this study was to asses the effectiveness of STN DBS on cognitive-? motor performance during a lower extremity task. 15 advanced PD patients, of which seven presented PIGD symptoms, were tested under single-? and dual-? task conditions. All patients were bilaterally implanted with STN DBS and had stable parameters as determined through typical clinical programming for at least 6 moths prior to study enrollment. Patients were assessed off anti-? parkinsonian medication under two DBS settings; Off DBS and On DBS. In each condition, patients performed a working memory task (n-? back) and a postural stability task (quiet standing). During the dual task, patients performed the working memory and postural stability tasks simultaneously. DBS was effective in improving Unified Parkinson? ’s disease Rating Scale III scores relative to no stimulation. Cognitive functioning showed no difference between the two DBS conditions. Patients with PIGD symptoms were significantly less stable than patients with no PIGD symptoms for both On and Off DBS conditions. These data show that with the paradigm used in this study, PIGD symptoms continue to be refractory to DBS. Postural stability as assessed by quietly standing on a force platform may not have been challenging enough to evoke cognitive declines.
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Robust Data Fusion of Multimodal Sensory Information for Mobile Robots

Urban search and rescue (USAR) missions for mobile robots require reliable state estimation systems resilient to conditions given by the dynamically changing environment. We design and evaluate a data fusion system for localization of a mobile skid‐steer robot intended for USAR missions. We exploit a rich sensor suite including both proprioceptive (inertial measurement unit and tracks odometry) and exteroceptive sensors (omnidirectional camera and rotating laser rangefinder). To cope with the specificities of each sensing modality (such as significantly differing sampling frequencies), we introduce a novel fusion scheme based on an extended Kalman filter for six degree of freedom orientation and position estimation. We demonstrate the performance on field tests of more than 4.4 km driven under standard USAR conditions. Part of our datasets include ground truth positioning, indoor with a Vicon motion capture system and outdoor with a Leica theodolite tracker. The overall median accuracy of localization—achieved by combining all four modalities—was 1.2% and 1.4% of the total distance traveled for indoor and outdoor environments, respectively. To identify the true limits of the proposed data fusion, we propose and employ a novel experimental evaluation procedure based on failure case scenarios. In this way, we address the common issues such as slippage, reduced camera field of view, and limited laser rangefinder range, together with moving obstacles spoiling the metric map. We believe such a characterization of the failure cases is a first step toward identifying the behavior of state estimation under such conditions. We release all our datasets to the robotics community for possible benchmarking.
A NOVEL COMPARATIVE METHOD FOR IDENTIFYING SHIFTS IN THE RATE OF CHARACTER EVOLUTION ON TREES

Evolutionary biologists since Darwin have been fascinated by differences in the rate of trait‐evolutionary change across lineages. Despite this continued interest, we still lack methods for identifying shifts in evolutionary rates on the growing tree of life while accommodating uncertainty in the evolutionary process. Here we introduce a Bayesian approach for identifying complex patterns in the evolution of continuous traits. The method (auteur) uses reversible‐jump Markov chain Monte Carlo sampling to more fully characterize the complexity of trait evolution, considering models that range in complexity from those with a single global rate to potentially ones in which each branch in the tree has its own independent rate. This newly introduced approach performs well in recovering simulated rate shifts and simulated rates for datasets nearing the size typical for comparative phylogenetic study (i.e., ≥64 tips). Analysis of two large empirical datasets of vertebrate body size reveal overwhelming support for multiple‐rate models of evolution, and we observe exceptionally high rates of body‐size evolution in a group of emydid turtles relative to their evolutionary background. auteur will facilitate identification of exceptional evolutionary dynamics, essential to the study of both adaptive radiation and stasis.
Factors Affecting Learning of Concrete Nouns and Verbs in a Foreign Language

First language researchers have proposed dozens of explanations why infants across cultures seem to acquire more nouns than verbs among their earliest words. No such finding has been documented among adult foreign language learners. I wished to determine whether adults have greater difficulty learning verbs than nouns, and if so, why that could be.To investigate whether adult college students might learn concrete nouns or verbs better, I constructed and measured a list of noun and verb concepts, images, and auditory stimuli. I measured these stimuli on many dimensions with a mind to statistically control these extraneous factors when testing for differences in noun and verb learning (Study 1). In Studies 2 and 3 I trained participants with these words and tested their recognition of targets with multiple-choice tests. I then statistically controlled and measured the effects of measured and manipulated factors to see what confluence of factors affected word learning. While there was generally a noun bias effect, I found that methods of learning and delay qualified this effect (removing the noun bias at inferential learning, and reversing the word bias at one week), image media quality is of likely help to the learner, and cross-situational learning is greatly helpful. This dissertation concludes with a summary of findings and accounts of them. Although it remained partly unclear why nouns were generally learned better than verbs, Gleitman et al.'s (2006) surface variability hypothesis was taken as the most likely account for the noun bias observed among this sample of young adults.
Selective method combination in mixin-based composition

A mixin is a reusable module that provides uniform extensions and modifications to classes. It is an abstract subclass that is composable with a variety of superclasses. In mixin-based composition, however, the problem of accidental overriding arises. A method declared in a mixin may accidentally overrides its superclasses' method. To tackle this problem, we propose a new approach of method lookup that allows selective method combination; that is, when we have multiple methods with the same name and the same formal parameter types in a composition, we can select which method to execute, and which method is called when there exists a method call to super. This proposal is an extension of hygienic mixins with stronger expressive power. This proposal is implemented in McJava, an extension of Java with mixintypes. Its compilation is achieved by source code translation to Java thus making it runnable on a standard Java virtual machine.