Miracle-dz/UniFAR-FTUs huggingface dataset:
Three‐dimensional Modeling of the Various Volumes of Canines to Determine Age and Sex: A Preliminary Study

Abstract: Canines are usually used in anthropological and forensic sciences for sex and age determination. The best methods to estimate age are based on secondary dentine apposition, evaluated from periapical X‐rays. The aim of this study was to propose a new method of sex and age estimation using 3D models to obtain more precise predictions using tooth volumes. Fifty‐eight dental CT scans of patients aged 14–74 with a well‐balanced sex ratio composed the sample. One hundred and thirty‐three healthy canines were modeled (Mimics 12.0). The sample was divided into a training sample and a validation sample. An age formula was determined using the “pulp volume/tooth volume” ratio. Sex prediction was adjusted with total volumes. Applying the equations to the validation sample, no significant difference was found between the real and predicted ages, and 100% of the sex predictions were correct. This preliminary study gives interesting results, and this method is worth being tested on a larger data sample.
Discriminative Training for Large-Vocabulary Speech Recognition Using Minimum Classification Error

The minimum classification error (MCE) framework for discriminative training is a simple and general formalism for directly optimizing recognition accuracy in pattern recognition problems. The framework applies directly to the optimization of hidden Markov models (HMMs) used for speech recognition problems. However, few if any studies have reported results for the application of MCE training to large-vocabulary, continuous-speech recognition tasks. This article reports significant gains in recognition performance and model compactness as a result of discriminative training based on MCE training applied to HMMs, in the context of three challenging large-vocabulary (up to 100 k word) speech recognition tasks: the Corpus of Spontaneous Japanese lecture speech transcription task, a telephone-based name recognition task, and the MIT Jupiter telephone-based conversational weather information task. On these tasks, starting from maximum likelihood (ML) baselines, MCE training yielded relative reductions in word error ranging from 7% to 20%. Furthermore, this paper evaluates the use of different methods for optimizing the MCE criterion function, as well as the use of precomputed recognition lattices to speed up training. An overview of the MCE framework is given, with an emphasis on practical implementation issues
Tropomodulin: a cytoskeletal protein that binds to the end of erythrocyte tropomyosin and inhibits tropomyosin binding to actin

Human erythrocytes contain a Mr 43,000 tropomyosin-binding protein that is unrelated to actin and that has been proposed to play a role in modulating the association of tropomyosin with spectrin-actin complexes based on its stoichiometry in the membrane skeleton of one Mr 43,000 monomer per short actin filament (Fowler, V. M. 1987. J. Biol. Chem. 262:12792-12800). Here, we describe an improved procedure to purify milligram quantities to 98% homogeneity and we show that this protein inhibits tropomyosin binding to actin by a novel mechanism. We have named this protein tropomodulin. Unlike other proteins that inhibit tropomyosin-actin interactions, tropomodulin itself does not bind to F- actin. EM of rotary-shadowed tropomodulin-tropomyosin complexes reveal that tropomodulin (14.5 +/- 2.4 nm [SD] in diameter) binds to one of the ends of the rod-like tropomyosin molecules (33 nm long). In agreement with this observation, Dixon plots of inhibition curves demonstrate that tropomodulin is a non-competitive inhibitor of tropomyosin binding to F-actin (Ki = 0.7 microM). Hill plots of the binding of the tropomodulin-tropomyosin complex to actin indicate that binding does not exhibit any positive cooperativity (n = 0.9), in contrast to tropomyosin (n = 1.9), and that the apparent affinity of the complex for actin is reduced 20-fold with respect to that of tropomyosin. These results suggest that binding of tropomodulin to tropomyosin may block the ability of tropomyosin to self-associate in a head-to-tail fashion along the actin filament, thereby weakening its binding to actin. Antibodies to tropomodulin cross-react strongly with striated muscle troponin I (but not with troponin T) as well as with a nontroponin Mr 43,000 polypeptide in muscle and in other nonerythroid cells and tissues, including brain, lens, neutrophils, and endothelial cells. Thus, erythrocyte tropomodulin may be one member of a family of tropomyosin-binding proteins that function to regulate tropomyosin- actin interactions in non-muscle cells and tissues.
On the Uniform One-dimensional Fragment

The uniform one-dimensional fragment of first-order logic, U1, is a recently introduced formalism that extends two-variable logic in a natural way to contexts with relations of all arities. We survey properties of U1 and investigate its relationship to description logics designed to accommodate higher arity relations, with particular attention given to DLR_reg. We also define a description logic version of a variant of U1 and prove a range of new results concerning the expressivity of U1 and related logics.
Fluoxetine versus Vitex agnus castus extract in the treatment of premenstrual dysphoric disorder

Clinical trials have demonstrated that serotonin reuptake inhibitors (SRIs) and the extract of Vitex agnus castus are effective for the treatment of premenstrual dysphoric disorder (PMDD). However, to the best of our knowledge, there has been no study comparing the efficacy of the SRIs with Vitex agnus castus (AC) extract. Therefore, the aim of the present study was to compare the efficacy of fluoxetine, a selective serotonin reuptake inhibitor (SSRI), with that of the AC extract, a natural choice. After a period of 2 screening months to screen the patients for suitability, 41 patients with PMDD according to DSM‐IV were recruited into the study. The patients were randomized to fluoxetine or AC for 2 months of single‐blind, rater‐ blinded and prospective treatment period. The outcome measures included the Penn daily symptom report (DSR), the Hamilton depression rating scale (HAM‐D), and the clinical global impression‐severity of illness (CGI‐SI) and ‐improvement (CGI‐I) scales. At endpoint, using the clinical criterion for improvement, a similar percentage of patients responded to fluoxetine (68.4%, n = 13) and AC (57.9%, n = 11). There was no statistically significant difference between the groups with respect to the rate of responders. This preliminary study suggests that patients with PMDD respond well to treatment with both fluoxetine and AC. However, fluoxetine was more effective for psychological symptoms while the extract diminished the physical symptoms. Copyright © 2002 John Wiley & Sons, Ltd.
Enhanced Antitumor Efficacy of a DR5-Specific TRAIL Variant over Recombinant Human TRAIL in a Bioluminescent Ovarian Cancer Xenograft Model

Purpose: Recombinant human tumor necrosis factor-related apoptosis-inducing ligand (rhTRAIL) is clinically evaluated as novel anticancer drug. rhTRAIL-DR5, a rhTRAIL variant that specifically binds to DR5 receptor, has recently been developed. We investigated whether rhTRAIL-DR5 is more efficient than rhTRAIL in combination with cisplatin in DR5-expressing human A2780 ovarian cancer cells. Design: Effect of cisplatin alone or in combination with rhTRAIL or rhTRAIL-DR5 on DR5 surface expression, apoptosis, and cell survival of A2780 was measured. Biodistribution analysis was done in mice with 125I-rhTRAIL administered intravenously versus intraperitoneally. Antitumor efficacy of rhTRAIL-DR5 versus rhTRAIL was determined in an intraperitoneally growing bioluminescent A2780 xenograft model. Results: Cisplatin strongly enhanced DR5 surface expression. Both rhTRAIL and rhTRAIL-DR5 in combination with cisplatin induced high levels of caspase-3 activation, apoptosis, and cell kill, with rhTRAIL-DR5 being most potent. Intraperitoneal administration of 125I-rhTRAIL resulted in a 1.7-fold higher area under the curve in serum, increased tumor exposure, and more caspase-3 activation in the tumor than intravenous administration. Intraperitoneal administration of rhTRAIL-DR5 delayed A2780 tumor progression, reflected in a mean light reduction of 68.3% (P = 0.015), whereas rhTRAIL or rhTRAIL-DR5 plus cisplatin resulted in 85% (P = 0.003) and 97% (P = 0.002) reduction compared with A2780 tumor progression in vehicle-treated animals. Combination of rhTRAIL-DR5 with cisplatin was more effective than cisplatin alone (P = 0.027). Conclusion: rhTRAIL-DR5 was superior over rhTRAIL in vitro and in vivo against DR5-expressing ovarian cancer also in combination with cisplatin. Intraperitoneal administration of rhTRAIL-DR5 warrants further exploration in ovarian cancer.
Regional cerebral blood flow in apoplexy without arterial occlusion

IN A PREVIOUS STUDY we reported on regional cerebral blood flow in patients with apoplexy due to occlusion of the middle cerebral artery.l The xenon 133 injection method was used and the studies included observations of the regional flow response of the brain to changes of the arterial blood pressure and of the arterial pC0, and to injection of theophylline. Focal ischemia or focal hyperemia or both were found in all patients, combined with focal vasoparalysis in most of them. This group of middle cerebral artery occlusions was studied with the aim of collecting information on the regional cerebral blood flow and its regulation in a more welldefined group of apoplexies than in earlier reports.2-6 In the present paper, we have aimed at studying another fairly uniform group of apoplexies, i.e., patients without angiographic evidence of arterial occlusion and all with hemiparetic symptoms of more than twenty-four hours’ duration (studies in more transitory attacks will be reported separately). T The flow studies were made at varying time intervals after the acute onset of the disease, and this proved to be of decisive importance for the regional blood flow derangement seen.
Urban attractors: Discovering patterns in regions of attraction in cities

Understanding the dynamics by which urban areas attract visitors is important in today’s cities that are continuously increasing in population towards higher densities. Identifying services that relate to highly attractive districts is useful to make policies regarding the placement of such places. Thus, we present a framework for classifying districts in cities by their attractiveness to daily commuters and relating Points of Interests (POIs) types to districts’ attraction patterns. We used Origin-Destination matrices (ODs) mined from cell phone data that capture the flow of trips between each pair of places in Riyadh, Saudi Arabia. We define the attraction profile for a place based on three main statistical features: The number of visitors a place received, the distribution of distance traveled by visitors on the road network, and the spatial spread of locations from where trips started. We used a hierarchical clustering algorithm to classify all places in the city by their features of attraction. We discovered three main types of Urban Attractors in Riyadh during the morning period: Global, which are significant places in the city, Downtown, which contains the central business district, and Residential attractors. In addition, we uncovered what makes districts possess certain attraction patterns. We used a statistical significance testing approach to quantify the relationship between Points of Interests (POIs) types (services) and the patterns of Urban Attractors detected.
Finding Predominant Word Senses in Untagged Text

In word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely powerful because the distribution of the senses of a word is often skewed. The problem with using the predominant, or first sense heuristic, aside from the fact that it does not take surrounding context into account, is that it assumes some quantity of hand-tagged data. Whilst there are a few hand-tagged corpora available for some languages, one would expect the frequency distribution of the senses of words, particularly topical words, to depend on the genre and domain of the text under consideration. We present work on the use of a thesaurus acquired from raw textual corpora and the WordNet similarity package to find predominant noun senses automatically. The acquired predominant senses give a precision of 64% on the nouns of the SENSEVAL-2 English all-words task. This is a very promising result given that our method does not require any hand-tagged text, such as SemCor. Furthermore, we demonstrate that our method discovers appropriate predominant senses for words from two domain-specific corpora.
The “Intelligent Container”—A Cognitive Sensor Network for Transport Management

The “Intelligent Container” is a sensor network used for the management of logistic processes, especially for perishable goods such as fruit and vegetables. The system measures relevant parameters such as temperature and humidity. The concept of “cognitive systems” provides an adequate description of the complex supervision tasks and sensor data handling. The cognitive system can make use of several algorithms in order to estimate temperature related quality losses, detect malfunctioning sensors, and to control the sensor density and measurement intervals. Based on sensor data, knowledge about the goods, their history and the context, decentralized decision making is realized by decision support tools. The amount of communication between the container and the headquarters of the logistic company is reduced, while at the same time the quality of the process control is enhanced. The system is also capable of self-evaluation using plausibility checking of the sensor data.
Developing a Professional Pathway in Health Equity to Facilitate Curricular Transformation at the University of Michigan Medical School

Problem Medical schools are challenged to realign curricula to address society’s needs in a rapidly changing environment, and to support new instruction and assessment methods that require substantial faculty time. Approach In 2010, the University of Michigan Medical school began planning the Global Health and Disparities Path of Excellence (GHD Path), an optional co-curriculum for students interested in health disparities, with explicit goals to (1) draw attention to the school’s social mission; (2) test new, faculty-intensive methods of learning and assessment for all students; and (3) serve as a template for additional co-curricular paths. Outcomes Intended outcomes of the program include enhancing students’ competency in leadership related to ameliorating health disparities and the study institution’s ability to plan feasible and effective schoolwide reforms in self-directed learning, faculty advising systems, narrative-based feedback for goal setting, Web-based student portfolios, and additional Paths of Excellence. Next Steps During academic year 2013–2014, the GHD Path is adding more community-based experiences. The faculty development and support model will be streamlined to decrease resources required for program development while retaining key features of the advising system. Lessons from the GHD Path are central to planning schoolwide reform of instructional methods, faculty advising, and student portfolios. The use of a small-scale program to pilot new ideas to inform longer-term, larger-scale changes at our institution might prove useful to other schools striving to meet societal needs while implementing innovative methods of instruction and assessment.
Hierarchical Value Cache Encoding for Off-Chip Data Bus

Off-chip data bus consumes a significant part of system power. Recent works use small caches (value cache) at each side of the off-chip data bus, and transmit cache indexes instead of data values to reduce bus switching activity. A larger VC has a higher VC hit rate, but it also incurs more switching activity on a VC hit. In this paper, we propose the hierarchical VC design concept that provides a good tradeoff between VC capacity and bus switching activity. Our experimental results show that the proposed hierarchical VC design reduces the off-chip data bus energy by 60.2%
Antibiotic Inducibility of the mexXY Multidrug Efflux Operon of Pseudomonas aeruginosa: Involvement of the MexZ Anti-Repressor ArmZ

Expression of the mexXY multidrug efflux operon in wild type Pseudomonas aeruginosa is substantially enhanced by the ribosome-targeting antimicrobial spectinomycin (18-fold) and this is wholly dependent upon the product of the PA5471 gene. In a mutant strain lacking the mexZ gene encoding a repressor of mexXY gene expression, expression of the efflux operon increases modestly (5-fold) and is still responsive (18-fold) to spectinomycin. Spectinomycin induction of mexXY expression in the mexZ mutant is, however, independent of PA5471 suggesting that PA5471 functions as an anti-repressor (dubbed ArmZ for anti-repressor MexZ) that serves only to modulate MexZ's repressor activity, with additional gene(s)/gene product(s) providing for the bulk of the antimicrobial-inducible mexXY expression. Consistent with PA5471/ArmZ functioning as a MexZ anti-repressor, an interaction between MexZ and ArmZ was confirmed using a bacterial 2-hybrid assay. Mutations compromising this interaction (P68S, G76S, R216C, R221W, R221Q, G231D and G252S) were identified and localized to one region of an ArmZ structural model that may represent a MexZ-interacting domain. Introduction of representative mutations into the chromosome of P. aeruginosa reduced (P68S, G76S) or obviated (R216C, R2211W) antimicrobial induction of mexXY gene expression, rendering the mutants pan-aminoglycoside-susceptible. These data confirm the importance of an ArmZ-MexZ interaction for antimicrobial-inducible mexXY expression and intrinsic aminoglycoside resistance in P. aeruginosa.
Location Tracking in a Wireless Sensor Network by Mobile Agents and Its Data Fusion Strategies

The wireless sensor network is an emerging technology that may greatly facilitate human life by providing ubiquitous sensing, computing, and communication capability, through which people can more closely interact with the environment wherever he/she goes. To be context-aware, one of the central issues in sensor networks is location tracking, whose goal is to monitor the roaming path of a moving object. While similar to the location-update problem in PCS networks, this problem is more challenging in two senses: (1) there are no central control mechanism and backbone network in such environment, and (2) the wireless communication bandwidth is very limited. In this paper, we propose a novel protocol based on the mobile agent paradigm. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object. The agent is mobile since it will choose the sensor closest to the object to stay. The agent may invite some nearby slave sensors to cooperatively position the object and inhibit other irrelevant (i.e., farther) sensors from tracking the object.As a result, the communication and sensing overheads are greatly reduced. Our prototyping of the location-tracking mobile agent based on IEEE 802.11b NICs and our experimental experiences are also reported.
Susceptibility of Immature and Mature Langerhans Cell-Type Dendritic Cells to Infection and Immunomodulation by Human Cytomegalovirus

ABSTRACT Human cytomegalovirus (CMV) infection initiates in mucosal epithelia and disseminates via leukocytes throughout the body. Langerhans cells (LCs), the immature dendritic cells (DCs) that reside in epithelial tissues, are among the first cells to encounter virus and may play important roles in the immune response, as well as in pathogenesis as hosts for viral replication and as vehicles for dissemination. Here, we demonstrate that CD34+ progenitor cell-derived LC-type DCs exhibit a differentiation state-dependent susceptibility to CMV infection. In contrast to the small percentage (3 to 4%) of the immature LCs that supported infection, a high percentage (48 to 74%) of mature, LC-derived DCs were susceptible to infection with endotheliotropic strains (TB40/E or VHL/E) of CMV. These cells were much less susceptible to viral strains AD169varATCC, TownevarRIT3, and Toledo. When exposed to endotheliotropic strains, viral gene expression (IE1/IE2 and other viral gene products) and viral replication proceeded efficiently in LC-derived mature DCs (mDCs). Productive infection was associated with downmodulation of cell surface CD83, CD1a, CD80, CD86, ICAM-1, major histocompatibility complex (MHC) class I, and MHC class II on these cells. In addition, the T-cell proliferative response to allogeneic LC-derived mDCs was attenuated when CMV-infected cultures were used as stimulators. This investigation revealed important characteristics of the interaction between CMV and the LC lineage of DCs, suggesting that LC-derived mDCs are important to viral pathogenesis and immunity through their increased susceptibility to virus replication and virus-mediated immune escape.
Monitoring Kinematic Changes With Fatigue in Running Using Body-Worn Sensors

In this paper, we investigate monitoring of kinematic changes evoked by fatigue in running using wearable technology. Movement data were recorded with ETHOS devices. ETHOS is the ETH Orientation Sensor, a customized inertial measurement unit for unconstrained monitoring of human movement. We perform two real-world experiments, in which 21 runners of different skill levels participated. The real-world experiments capture two exhausting 45-min runs: one on a treadmill and one on a conventional outdoor track. We describe and evaluate algorithms to extract kinematic parameters from the sensor data. We identified parameters that change with fatigue for all runners, ones that change for runners of distinct skill levels, and ones that are dependent on an individual's running technique. Overall, we found that observations from treadmill running are not always generalizable to outdoor running. We, thus, argue for using wearable technology to provide athletes and trainers with continuous, quantitative objective measurements of running technique. These could be used to further gain insight into the complex relationship of running kinematics, injury risk, fatigue, and running economy.
Identification of corn and cotton fields using multi-temporal Spot6 NDVI data

In this research, parcel based identification of cotton and corn fields was conducted using single dated and multi-temporal SPOT6 NDVI images in three selected districts (Harran, Ceylanpinar and Viransehir) within Sanliurfa, Turkey. Four different applications were conducted in order to find out the most accurate method for the identification of spatial distribution and crop type of agricultural parcels. NDVI images for three different data acquisition dates for SPOT6 were produced, and then object-based classification approach was applied to multi-temporal NDVI image to accurately identify corn, and cotton fields in parcel level for the first application. For the next three applications, three different single date SPOT 6 images, which were acquired in June, July and September, were classified by using object based classification approach for identification of same crop types. Accuracy assessments for all four applications were conducted using confusion matrix and kappa statistics to analyze the accuracy of the proposed approaches.