Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-Associated Molecular Changes in the Kidney in Aged Mice

Background. Aging is a multifactorial process characterized by a progressive decline in physiological function. Decreased kidney function is associated with cardiovascular disease and mortality. Therefore, increasing our insight into kidney aging by understanding the anatomic, physiologic, and pathologic changes of aging in the kidney is important to prevent disastrous outcomes in elderly people. Methods. Male two-, 12-, and 24-month-old C57/BL6 mice were used in this study. We measured histological change, oxidative stress, and aging-related protein expression in the kidneys. Results. Twenty-four-month-old mice displayed increased albuminuria. Creatinine clearance decreased with aging, although this was not statistically significant. There were increases in mesangial volume and tubulointerstitial fibrosis in 24-month-old mice. There were also increases in F4/80 expression and in apoptosis detected by TUNEL assay. Urine isoprostane excretion increased with aging and SOD1 and SOD2 were decreased in 24-month-old mice. Oxidative stress may be mediated by a decrease in Sirt1, PGC-1α, ERR-1α, and PPARα expression. Klotho expression also decreased. Conclusions. Our results demonstrate that Sirt1 was decreased with aging and may relate to changed target molecules including PGC-1α/ERR-1α signaling and PPARα. Klotho can also induce oxidative stress. Pharmacologically targeting these signaling molecules may reduce the pathologic changes of aging in the kidney.
Surgery for temporal lobe epilepsy in Semarang, Indonesia: The first 56 patients with follow up longer than 12 months

Until October 2005, surgery were performed for 76 intractable temporal lobe epilepsy patients. Among them, 56 patients had follow-up of 12-76 months. The patients consisted of 35 males and 21 females, age between 3-38 year-old. Magnetic Resonance Imaging diagnoses were hippocampal sclerosis in 50 patients, temporal lobe tumor in 3 patients, hemispheric hemiatrophy, calcified hippocampal lesion and normal imaging one patient each. Intracranial subdural grid EEG was performed in the patient with normal imaging. Psychological evaluation was performed in all patients, while Wada test was performed on patients with left-sided lesion. All patients underwent anterior temporal lobectomy. Seizure free (Engel’s I) was seen on 46 patients (82%). Six patients (11%) had less than 2 seizures per year (Engel’s II). Seizure decreased by more than 75% (Engel’s III) in 4 patients (7%). There was a trend with increased number of patients with Engel’s II and III with longer duration of seizures. Complications were extradural empyema in 5 patients (9%), depression in 2 patients (4%), transient hemiparesis in one patient (2%). Thirty-one patients were able to withdraw the antiepileptic drugs. In conclusion, epilepsy surgery can achieve good results in developing countries.
NEIL1 excises 3′ end proximal oxidative DNA lesions resistant to cleavage by NTH1 and OGG1

Base excision repair is the major pathway for the repair of oxidative DNA damage in human cells that is initiated by a damage-specific DNA glycosylase. In human cells, the major DNA glycosylases for the excision of oxidative base damage are OGG1 and NTH1 that excise 8-oxoguanine and oxidative pyrimidines, respectively. We find that both enzymes have limited activity on DNA lesions located in the vicinity of the 3′ end of a DNA single-strand break, suggesting that other enzymes are involved in the processing of such lesions. In this study, we identify and characterize NEIL1 as a major DNA glycosylase that excises oxidative base damage located in close proximity to the 3′ end of a DNA single-strand break.
Trusted virtual machine monitor-based group signature architecture

Group communication is an important technique for many network computing applications. In group communication, a member in a group sends a message to others normally by multicast. Group signature guarantees the integrity of the exchanged data and provides source authentication. In a virtual machine (VMs) based computing system, a virtual machine monitor (VMM) allows applications to run in different VMs strongly isolated from each other. A trusted VMM (TVMM) based platform can provide stronger security protection for group signature systems than traditional computing platforms can. The authors first introduce a TVMM-based group signature architecture and a TVMM security protection mechanism for group signature components. Then, the authors propose a group signature scheme using the function of message checking based on the discrete logarithm problem. Finally, the authors prove the correctness of the group signature scheme and analyse its security in virtual computing environments.
Analysis on Body Image Perception Among Pupils in Urban Beijing

Objective To investigate the body image perceptions among pupils in urban Beijing, so as to offer evidence for development of intervention measures towards childhood obesity.Methods A total of 4 428 children aged 8-14(2 112 girls and 2 316 boys) were recruited by two-stage cluster sampling method. Body image was assessed by Ma figural stimuli. Their weight and height were also measured at the same time.Results The prevalence rates of overweight and obesity were 13.1% and 14.4%, respectively. The mean of ideal image score for boys (3.5) was higher than for girls (4.4). The means of body dissatisfaction scores were 1.0 and 1.3 for boys and girls respectively. Girls' body dissatisfaction scores were significantly higher than boys'. The body dissatisfaction scores across different weight status were: obesityoverweightnon-overweight. The standard body image scores of boys were significantly higher than the scores of girls. About 6.6% and 1.0% children chose the heaviest silhouette as their self-body image and ideal body image respectively. Conclusion The body image perception among children in urban Beijing is partly consistent with that in west countries, but children in urban Beijing are more tolerant of obesity. Considering children's body image perception, effective childhood obesity intervention measures should be implemented.
Research on energy regeneration and effect of dynamic characteristics of secondary control swing for hydraulic excavator system

In the modern era, the demand of energy saving is increasing more and more while the natural resources have been exhausted. Among various possibilities, some methods to recuperate energy during vehicle swing motion have been widely examined. After providing required drastic design changes, electric and hydraulic hybrids designs have shown a great improvement in fuel efficiency. The rotating movement of excavator is called swing or slew and is driven hydraulically. The swing drive is hence driven by a hydraulic motor creating a rotating motion. Following the movement of a joystick, the pump is controlled to match the spool positions, swiveling out. In the proposed system, swing braking time the remaining fluid will save as energy by a simple accumulator. This remaining save energy will be used in the system from accumulator. The proposed system is considered as secondary by using two combination of transformer (motor & pump combination) and have some dissimilarities from the conventional swing system. Furthermore, the paper simulates variable inertia and show the effect of variable moment of inertia in different simulation result. The proposed system will be developed in AMESim software. The proposed system will be more efficient in saving energy.
A Formal Model for Firewall Testing

Firewalls are hardware and software systems that protect a corporate network from attacks coming from the outside Internet. Despite their critical role, rewall systems are tested without well-deened and eeective methodologies. In particular, eld testing is performed using simple checklists of vulnerabilities without taking into account the particular topology and conngu-ration of the rewall's target operational environment. We propose a rewall testing methodology based on a formal model of networks that allows the test engineer to model the network environment of the rewall system , to prove formally that the topology of the network veriies the suucient conditions for protection against attacks, and to build test cases to verify that protec-tions are actually in place.
Liquidity Constrained Competing Auctions

When goods are sold through competing auctions, what e¤ect does monetary policy have on the equilibrium allocation? To answer, we extend the competing auctions framework in several ways: buyers choose how much money they bring to an auction, the quantities traded at the auctions are endogenous, and sellers can charge a fee (either positive or negative) to buyers participating in their auction. We present two di¤erent speci? cations of the model. In the ? rst model, sellers post a quantity they wish to sell and a fee, and allow the price to be determined by an auction. In the second model, sellers post a price and a fee and allow the quantity sold to be determined by an auction. When sellers post a quantity and buyers bid prices, the Friedman rule implements the ? rst best and, in this case, no fee is charged by sellers. Sellers charge buyers a participation fee as soon as the nominal interest rate is positive, and marginal increments in money growth decrease both the posted quantity and buyers? entry. The use of auction fees reduces welfare in this environment. When sellers post a price and buyers bid quantities, the Friedman rule is optimal but does not yield the ? rst best as agents trade an ine¢ ciently low quantity in multilateral matches and an ine¢ ciently high quantity in pairwise matches. Marginal increments in money growth decrease the posted real price and the quantities traded. When the interest rate is low, sellers pay buyers who participate in their auction, which increases welfare. When the interest rate is high, sellers charge buyers who participate in their auction, which reduces welfare.
Utilisation des Méthodes d'Apprentissage Ensembliste dans le Datamining Distribué

Le datamining distribue est ne du besoin de traiter des donnees qui peuvent etre d'une part tres volumineuses, et/ou eventuellement distribuees geographiquement a travers plusieurs sites. Les methodes d'apprentissage ensembliste en tant que techniques prometteuses en terme de precision, et offrant aussi un aspect ‘distribue', peuvent etre adaptees aux contraintes du datamining distribue. Nous presentons dans cet article les differentes approches permettant d'appliquer les methodes ensemblistes dans le (.)
Robust endpoint detection for in-car speech recognition

The endpoint detection plays a significantly important role in the front end processing of speech recognition. It is very difficult, however, to precisely locate endpoints on the input utterance to be free on non-speech regions because of unpredictable background noise. This paper proposes a novel approach that finds robust features for better endpoint detection in a noisy in-car environment. In the proposed method, we integrate both the widely used energy and entropy [2], [6] to form a new feature that possesses advantages of each individual while compensating the drawback of each other. By monitoring the variation of the extracted new features, more precise endpoints can be found. Experimental results present that this algorithm outperforms the energy-based algorithms in both accuracy of boundary point detection and recognition performance under a real in-car noisy environment. The result of accuracy improvement shows 10% higher comparing with energy-based algorithm.
Modelling modern processors using FEM and compact model — A comparative study

A variety of thermal models has been proposed to predict the temperatures inside modern processors. In this paper, we describe and compare two such approaches, a detailed FEM-based simulation and a simpler architectural compact model. It is shown that both models provide comparable results when it comes to predicting the maximal temperature, however there are also non-negligible differences when estimating thermal gradients within a chip.
Hierarchical RLE level set: A compact and versatile deformable surface representation

This article introduces the Hierarchical Run-Length Encoded (H-RLE) Level Set data structure. This novel data structure combines the best features of the DT-Grid (of Nielsen and Museth [2004]) and the RLE Sparse Level Set (of Houston et al. [2004]) to provide both optimal efficiency and extreme versatility. In brief, the H-RLE level set employs an RLE in a dimensionally recursive fashion. The RLE scheme allows the compact storage of sequential nonnarrowband regions while the dimensionally recursive encoding along each axis efficiently compacts nonnarrowband planes and volumes. Consequently, this new structure can store and process level sets with effective voxel resolutions exceeding 5000 × 3000 × 3000 (45 billion voxels) on commodity PCs with only 1 GB of memory. This article, besides introducing the H-RLE level set data structure and its efficient core algorithms, also describes numerous applications that have benefited from our use of this structure: our unified implicit object representation, efficient and robust mesh to level set conversion, rapid ray tracing, level set metamorphosis, collision detection, and fully sparse fluid simulation (including RLE vector and matrix representations.) Our comparisons of the popular octree level set and Peng level set structures to the H-RLE level set indicate that the latter is superior in both narrowband sequential access speed and overall memory usage.
The Role of Anticipated Emotions in Purchase Intentions

Key personal inputs to decision making reside in expectations about whether a purchase or nonpurchase will make one feel better. Integrating several theoretical approaches, this research proposes a holistic framework formed by four kinds of anticipated emotions (AEs) resulting from the crossing of positive- or negative-valenced emotions with action or inaction. Specifically, this research proposes that consumers under a purchase scenario tend to consider positive and negative AEs of both purchase and nonpurchase in their decisions. Research in this area to date has been sparse and focused mostly on AEs with regard to purchase, but not nonpurchase. The results of four studies confirm that AEs influence purchase decisions in a coordinated way depending on their instrumentality, motivating purchase or nonpurchase. AEs also partially mediate the effect of outcome valence on purchase decisions. Taking the status quo bias as a theoretical basis, this work proposes that the amount of information of favorable and unfavorable outcome messages has a greater influence on AEs motivating purchase than AEs motivating nonpurchase. Finally, future research lines are proposed to expand the use of this fourfold framework and more generally to understand the role of forward-looking emotions in decision processes.
Generating Hard Satisfiable Scheduling Instances

We present a random generator of partially complete round robin timetables that produces exclusively satisfiable instances, and provide experimental evidence that there is an easy-hard-easy pattern in the computational difficulty of completing partially complete timetables as the ratio of the number of removed entries to the total number of entries of the timetable is varied. Timetables in the hard region provide a suitable test-bed for evaluating and fine-tuning local search algorithms.
Prototype design of hybrid multi-core architecture for real-time application

New tendencies envisage multi-core as a promising solution for real-time application. And the key challenge is how to improve the communication efficiency. In this paper, we propose a new multi-core architecture, which adopts the hybrid interconnection composed of both bus-based and NoC architecture, and we also introduce several technologies to improve its communication efficiency. Adopting the new architecture, we design a multi-core prototype chip which integrates 12 ARM compatible cores. Further, we design a real-time fade-in-fade-out video demo system base on the prototype chip and evaluate the communication performance. The hybrid multi-core prototype chip runs at 90MHZ, and can accomplish real-time fade-in-fade-out processing of 4 lane video (320×240, 30fps).
Hierarchical Cell Relay Scheme with GPS for Mobile Ad Hoc Networks

Many location-based routing protocols have been developed recently, and have been demonstrated to be scalable and efficient for packet routing in mobile ad hoc networks. Using location-based routing requires that a node obtains the node position with which it wants to communicate. This task is generally achieved by a location service. This work presents a novel routing protocol, called hierarchical cell relay (HCR), with a location service. The network area is divided into a number of regular triangular regions, called cells. Nodes forward the packets by some chosen cells, and are classified to be three level hierarchical structures. The hierarchical approach of HCR makes it especially suited for high network density. Moreover, the traffic loads in HCR are shared by all nodes rather than just by some specific nodes, thus reducing overheads at high traffic loads. Simulation results indicate that HCR has better performance than location-aid routing (LAR), in terms of packet delivery ratio, end-to-end delay and overhead in high traffic load.
Pre‐breeding diet affects the allocation of yolk hormones in zebra finches Taeniopygia guttata

The ability of mothers to modify offspring phenotype to match prevailing environmental conditions is an important component of reproductive success, especially in variable environments. Pre-breeding conditions, such as food abundance, may have significant consequences for both the number and quality of offspring a female produces as well as her ability to rear the offspring. In an experiment where pre-breeding diet was manipulated, we investigated if allocation of yolk androgens (testosterone and 5 alpha-dihydrotestosterone) was related to the quality of diet experienced prior to breeding. Female zebra finches Taeniopygia guttata produced larger clutches on high quality diet than on low quality diet but with no differences in egg mass. Yolk androgen levels were repeatable within subsequent clutches of the same female and females did not change mean androgen content in eggs in relation to diet quality. However, within-in Clutch pattern of yolk testosterone and DHT changed with diet treatment. Testosterone and DHT decreased with laying order on the low quality diet but remained constant on the high quality diet. Differential yolk androgen allocation within the clutch may alter the competitive differences between chicks and provide females the possibility to adjust reproductive investment and offspring phenotype already at the egg stage. (Less)
Determining the specificity of nouns from text

In this work, we use a large text corpus to order nouns by their level of specificity. This semantic information can for most nouns be determined with over 80% accuracy using simple statistics from a text corpus without using any additional sources of semantic knowledge. This kind of semantic information can be used to help in automatically constructing or augmenting a lexical database such as WordNet.
Towards an Internal Numerical Taxonomy of Software Process Assessment Methods

Objectives: The main goal of this paper is the internal comparison and classification of software process assessment methods. Methods: This exploratory study used a new methodology, based on numerical taxonomy. Eight software process assessment methods (SCAMPI; RAPID; SPICE; EVALUATION; BOOTSTRAP; SA-SI; MMA, and CBA-IPI) were classified. For the study were used documents describing the assessment methods. Results: A data table with a final set of 112 characters; proximity matrices of methods from step 4, and the final result was a hierarchical taxonomy of the eight methods selected from a set of taxonomies (step 5) validated (step 6) for a significance level of 5%. Conclusions: The internals comparison and classification produced are preliminary and are in accordance with our perceptions about the internal relationships between the methods. From the taxonomy was concluded that the methods SCAMPI and Bootstrap are the closest, followed by CBA-IPI, RAPID and MMA, Evaluation, SA-SI and SPICE by this order. Because of the exploratory nature of the work, the need for more studies is pointed.
Salivary Genomics, Transcriptomics and Proteomics: The Emerging Concept of the Oral Ecosystem and their Use in the Early Diagnosis of Cancer and other Diseases

There is an increasingly growing interest world-wide for the genomics, transcriptomics and proteomics of saliva and the oral cavity, since they provide a non-invasive source of unprecedently rich genetic information. The complexity of oral systems biology goes much beyond the human genome, transcriptome and proteome revealed by oral mucosal cells, gingival crevicular fluid, and saliva, and includes the complexity of the oral microbiota, the symbiotic assembly of bacterial, fungal and other microbial flora in the oral cavity. In our review we summarize the recent information on oral genomics, transcriptomics and proteomics, of both human and microbial origin. We also give an introduction and practical advice on sample collection, handling and storage for analysis. Finally, we show the usefulness of salivary and oral genomics in early diagnosis of cancer, as well as in uncovering other systemic diseases, infections and oral disorders. We close the review by highlighting a number of possible exploratory pathways in this emerging, hot research field.
Optimal scanning for faster object detection

Recent years have seen the development of fast and accurate algorithms for detecting objects in images. However, as the size of the scene grows, so do the running-times of these algorithms. If a 128×102 pixel image requires 20 ms to process, searching for objects in a 1280×1024 image will take 2 s. This is unsuitable under real-time operating constraints: by the time a frame has been processed, the object may have moved. An analogous problem occurs when controlling robot camera that need to scan scenes in search of target objects. In this paper, we consider a method for improving the run-time of general-purpose object-detection algorithms. Our method is based on a model of visual search in humans, which schedules eye fixations to maximize the long-term information accrued about the location of the target of interest. The approach can be used to drive robot cameras that physically scan scenes or to improve the scanning speed for very large high resolution images. We consider the latter application in this work by simulating a “digital fovea” and sequentially placing it in various regions of an image in a way that maximizes the expected information gain. We evaluate the approach using the OpenCV version of the Viola-Jones face detector. After accounting for all computational overhead introduced by the fixation controller, the approach doubles the speed of the standard Viola-Jones detector at little cost in accuracy.