Miracle-dz/UniFAR-FTUs huggingface dataset:
Pretreatment with Cisplatin Enhances E7-Specific CD8+ T-Cell–Mediated Antitumor Immunity Induced by DNA Vaccination

Purpose: Because the combination of multiple modalities for cancer treatment is more likely to generate more potent therapeutic effects for the control of cancer, we have explored the combination of chemotherapy using cisplatin, which is routinely used in chemotherapy for advanced cervical cancer, with immunotherapy using DNA vaccines encoding calreticulin (CRT) linked to human papillomavirus type 16 E7 antigen (CRT/E7) in a preclinical model. Experimental Design: We characterized the combination of cisplatin with CRT/E7 DNA vaccine using different regimen for its potential ability to generate E7-specific CD8+ T-cell immune responses as well as antitumor effects against E7-expressing tumors. Results: Our results indicate that treatment of tumor-bearing mice with chemoimmunotherapy combining cisplatin followed by CRT/E7 DNA generated the highest E7-specific CD8+ T-cell immune response and produced the greatest antitumor effects and long-term survival as well as significant levels of E7-specific tumor-infiltrating lymphocytes compared with all the other treatment regimens. Furthermore, we found that treatment with cisplatin leads to the cell-mediated lysis of E7-expressing tumor cells in vitro and increased number of E7-specific CD8+ T-cell precursors in tumor-bearing mice. In addition, we observed that E7-specific CD8+ T cells migrate to and proliferate in the location of TC-1 tumors in mice treated with cisplatin. Conclusions: Thus, our data suggest that chemoimmunotherapy using cisplatin followed by CRT/E7 DNA vaccine is an effective treatment against E7-expressing tumors and may potentially be translated into the clinical arena.
Linear and Non-Linear Run Length Limited Codes

We compare achievable rates of binary linear and non-linear run length limited codes where the constraint is on the number of consecutive ones. We show that there is a significant loss in rate when linear codes are used. For non-linear codes, we present practical encoders with rates close to the theoretical limits. We show that our approach can be generalised to avoid arbitrary sequences in the data stream.
Intraepidermal nerve fibers are indicators of small-fiber neuropathy in both diabetic and nondiabetic patients.

OBJECTIVE Small-fiber neuropathies may be symptomatic yet escape detection by standard tests. We hypothesized that morphologic changes in intraepidermal nerves would correlate with clinical measures of small-fiber neuropathy. RESEARCH DESIGN AND METHODS We studied 25 diabetic and 23 nondiabetic patients with neuropathy defined by signs, symptoms, and quantitative testing and 20 control subjects. Skin biopsies were obtained from forearm, thigh, proximal leg, and distal leg, and nerves identified using immunofluorescence with antibody to protein gene product (PGP) 9.5. RESULTS Mean dendritic length (MDL) (P < 0.01) and intraepidermal nerve fiber density (IENF) (P < 0.001) progressively decreased from proximal to distal sites only in patients with neuropathy. There was a significant reduction in IENF when comparing control subjects and patient groups in the distal leg (P < 0.001). MDL was significantly decreased in the thigh (P < 0.005) and in the proximal (P < 0.01) and distal (P < 0.002) leg in patients compared with control subjects. IENF was not significantly altered in diabetic patients of <5 years' duration, but significantly decreased in patients with >5 years' duration. MDL showed a linear decrease with increasing duration of diabetes. Distal leg IENF showed significant negative correlations with warm (P < 0.02) and cold (P < 0.05) thermal threshold, heat pain (P < 0.05), pressure sense (P < 0.05), and neurological disability score total sensory (P < 0.03) and total neuropathy (P < 0.03) values. CONCLUSIONS IENF was not significantly altered in these patients at <5 years' duration of diabetes, but fell significantly after 5 years of diabetes. MDL exhibited a linear loss with time, suggesting a different mechanism of change. MDL and IENF together may prove a useful end point in therapeutic trials for neuropathy.
On Fairness , Delay and Signaling of Different Approaches to Real-time Congestion Control

This paper touches three different topics regarding congestion control for real-time flows. First the difference between loss-based, receive-side delay-based and send-side delay-based congestion control algorithms is discussed. Next the difficulties with self-fairness is discussed, focusing on a particular scenario where, for example, Receive-side Real-time Congestion Control (RRTCC) [1] is shown to have problems.
Towards real-time collaborative filtering for big fast data

The Web of people is highly dynamic and the life experiences between our on-line and "real-world" interactions are increasingly interconnected. For example, users engaged in the Social Web more and more rely upon continuous social streams for real-time access to information and fresh knowledge about current affairs. However, given the deluge of data items, it is a challenge for individuals to find relevant and appropriately ranked information at the right time. Having Twitter as test bed, we tackle this information overload problem by following an online collaborative approach. That is, we go beyond the general perspective of information finding in Twitter, that asks: "What is happening right now? ", towards an individual user perspective, and ask: "What is interesting to me right now within the social media stream? ". In this paper, we review our recently proposed online collaborative filtering algorithms and outline potential research directions.
Implementing a Leading Loads Performance Predictor on Commodity Processors

Modern CPUs employ Dynamic Voltage and Frequency Scaling (DVFS) to boost performance, lower power, and improve energy efficiency. Good DVFS decisions require accurate performance predictions across frequencies. A new hardware structure for measuring leading load cycles was recently proposed and demonstrated promising performance prediction abilities in simulation. This paper proposes a method of leveraging existing hardware performance monitors to emulate a leading loads predictor. Our proposal, LL-MAB, uses existing miss status handling register occupancy information to estimate leading load cycles. We implement and validate LL-MAB on a collection of commercial AMD CPUs. Experiments demonstrate that it can accurately predict performance with an average error of 2.7% using an AMD Opteron™4386 processor over a 2.2x change in frequency. LL-MAB requires no hardware- or application-specific training, and it is more accurate and requires fewer counters than similar approaches.
Stem cells, progenitors and myelin repair

Remyelination, the process by which new myelin sheaths are restored to demyelinated axons, represents one of the most compelling examples of adult multipotent progenitor cells contributing to regeneration of the injured central nervous system (CNS). This process can occur with remarkable efficiency in both clinical disease, such as multiple sclerosis, and in experimental models, revealing an impressive ability of the adult CNS to repair itself. However, the inconsistency of remyelination in multiple sclerosis, and the loss of axonal integrity that results from its failure, makes enhancement of remyelination an important therapeutic objective. Identifying potential targets will depend on a detailed understanding of the cellular and molecular mechanisms of remyelination. In this article we address two important issues. First, we consider the nature of the cell or cells that respond to demyelination and generate new oligodendrocytes, identifying current areas of uncertainty and addressing the role of adult CNS stem and progenitor cells. Second, we discuss the concept of adult progenitor activation following demyelination, focusing on the increased expression of (1) olig transcription factors, (2) bone morphogenetic proteins and (3) fyn, a member of the src‐family of tyrosine kinases.
Enhancing intrapreneurial skills of students through entrepreneurship education

Innovation orientation in a modern society is experiencing extensive complexity due to rise in globalization, revolutionary changes in technologies and standard of living. Intrapreneurship defined as the innovative initiatives undertaken inside an organization is an effective strategy to address these complexities systematically. Successful ideas within an organization occur due to the tireless persistence and practical imagination of intrapreneurs who are the smart innovators actively involved in the design and creation of new products, ventures and business models. Today there is an increasing global demand for such intrapreneurs and different universities are therefore adopting various entrepreneurship education and training programmes to cater to this. Pedagogy in higher education is also witnessing a significant rise in new interdisciplinary programmes specifically designed for non-business students such as art, engineering, and science students so as to develop their organizational management skills. This paper sheds light on these growing trends of different University programmes and examines their effectiveness. It utilizes an in-depth study of one such successful case: the MSc Engineering Management programme in the University of York, United Kingdom in its role of enhancing intrapreneurial skills of global students. This paper explores how this programme has successfully incorporated active and experiential learning tactics within its teaching modules to gradually train and build up the intrapreneurial skills for working in multidisciplinary teams and industries.
Joint relevance and freshness learning from clickthroughs for news search

In contrast to traditional Web search, where topical relevance is often the main selection criterion, news search is characterized by the increased importance of freshness. However, the estimation of relevance and freshness, and especially the relative importance of these two aspects, are highly specific to the query and the time when the query was issued. In this work, we propose a unified framework for modeling the topical relevance and freshness, as well as their relative importance, based on click logs. We use click statistics and content analysis techniques to define a set of temporal features, which predict the right mix of freshness and relevance for a given query. Experimental results on both historical click data and editorial judgments demonstrate the effectiveness of the proposed approach.
A robust linear MPC approach to online generation of 3D biped walking motion

A crucial part in biped walking motion generation is to ensure dynamic feasibility, which takes the form of a nonlinear constraint in the general case. Our proposition is to bound the nonlinear part of the dynamic feasibility constraint between some properly chosen extreme values. Making sure that this constraint is satisfied for the extreme values guarantees its satisfaction for all possible values in between. This follows a classical approach from robust nonlinear control theory, which is to consider a nonlinear dynamical system as a specific selection of a time-invariant Linear Differential Inclusion. As a result, dynamic feasibility can be imposed by using only linear constraints, which can be included in an efficient linear MPC scheme, to generate 3D walking motions online. Our simulation results show two major achievements: 1) walking motions over uneven ground such as stairs can be generated online, with guaranteed kinematic and dynamic feasibility, 2) walking on flat ground is significantly improved, with a 3D motion of the CoM closely resembling the one observed in humans.
Pleiotropic Control by Testosterone of a Learned Vocal Behavior and Its Underlying Neuroplasticity123

Abstract Steroid hormones coordinate multiple aspects of behavior and physiology. The same hormone often regulates different aspects of a single behavior and its underlying neuroplasticity. This pleiotropic regulation of behavior and physiology is not well understood. Here, we investigated the orchestration by testosterone (T) of birdsong and its neural substrate, the song control system. Male canaries were castrated and received stereotaxic implants filled with T in select brain areas. Implanting T solely in the medial preoptic nucleus (POM) increased the motivation to sing, but did not enhance aspects of song quality such as acoustic structure and stereotypy. In birds implanted with T solely in HVC (proper name), a key sensorimotor region of the song control system, little or no song was observed, similar to castrates that received no T implants of any sort. However, implanting T in HVC and POM simultaneously rescued all measures of song quality. Song amplitude, though, was still lower than what was observed in birds receiving peripheral T treatment. T in POM enhanced HVC volume bilaterally, likely due to activity-dependent changes resulting from an enhanced song rate. T directly in HVC, without increasing song rate, enhanced HVC volume on the ipsilateral side only. T in HVC enhanced the incorporation and recruitment of new neurons into this nucleus, while singing activity can independently influence the incorporation of new neurons into HVC. These results have broad implications for how steroid hormones integrate across different brain regions to coordinate complex social behaviors.
Deploy a 5G Network in Less Than 5 Minutes

We describe a demonstration run on R2lab, an anechoic chamber located at Inria Sophia Antipolis, France. The demonstration consists in deploying a standalone 5G network in less than 5 minutes. All the network components (base station, subscriber management, serving and packet gateways, network traffic analyzers) were run automatically using the nepi-ng experiment orchestration tool. Download and upload performance to the Internet from a commercial phone located in the anechoic chamber are shown.
Lessons from the Road: Travel, Lifewide Learning, and Higher Education

Programs across the higher education landscape, including tourism education, are increasingly embracing experiential learning approaches, as provided through field schools, study abroad trips, and international internships. Most work on the value of such programs has tended to start in the most obvious place, by focusing on the programs themselves, the experiences students have with them, and the outcomes that ensue. Lurking beneath work on organized study trips, however, are deeper questions about the connections between learning and travel itself. What is it about travel that promotes learning? Are there certain conditions of travel that tend to be relevant for facilitating particular kinds of learning, and even for potentially transforming the way people see themselves and the world? This article briefly summarizes the outcomes of an empirical study on the relationship between travel and learning, for the purpose of offering discussion regarding how the insights derived from this work might be useful in the development and management of educational travel programs, in order to facilitate transformational learning and empowerment among students.
Optimal base station placement and fixed channel assignment applied to wireless local area network projects

The project of a wireless local area network (WLAN) has two major issues: determining the best placement of the base stations (BS) and assigning the frequency channels for the stations. The correct BS placement minimizes the number of stations necessary to cover the desired attendance area, reducing installation costs. The channel assignment determines the frequency band to be used by each BS, minimizing interference signals between them and improving the network throughput. This work relates a real experience where we applied the concepts of two outdoor environment classic problems, the optimal base placement problem for indoor environments and the fixed channel assignment problem, to build a wireless local area network in an indoor environment. We describe the hardware we used, the integer linear programming models developed and the results obtained.
The Relationship Between Client-Established Goals and Outcome in Counseling

Abstract : Use of goals as outcome measures has received some attention in the counseling literature, but little attention has been paid to the role of goal setting as a potential catalyst for change to enhance counseling outcome. Using a goal construct framework developed by Austin and Vancouver (1996), this research was a preliminary study to consider the relationship of client-established counseling goal content and dimensions (difficulty, specificity, and temporal range) to counseling outcome as measured by the Outcome Questionnaire (Lambert & Burlingame, 1996). Counseling goals of 51 participants (aged 18-25 years) were rated using the Ford and Nichols Taxonomy of Human Goals (Ford & Nichols, 1987; Ford, 1992); this research provides evidence of empirical validity for the use of this taxonomy to categorize counseling goals. A series of chi-square analyses, analyses of variance and linear regression analyses revealed relationships between goal specificity and counseling outcome. Client established counseling goal content was not related to counseling outcome. However, regardless of goal content, having specific goals was related to better counseling outcome, and if the content of the counseling goal had external consequences, it was critical to counseling outcome that the goal be set specifically. Counseling goals with internal consequences were more specific than those with external consequences, and in particular, affective goals were more specific than self-assertive social relationship goals. These findings are evidence that setting specific counseling goals can serve as a catalyst to increase the change occurring in counseling.
Zero-forcing transceiver design in the multi-user MIMO cognitive relay networks

The transceiver design in a cognitive radio networks is studied, where all nodes are deployed with multiple antennas. A primary point-to-point MIMO link is authorized to utilize the spectrum. Ignoring the secondary users, the primary transmitter and receiver are designed based on the traditional singular value decomposition method. The secondary users consist of multiple source-destination pairs, assisted by multiple two-hop non-regenerative relays. The transceivers of the secondary users are supposed to cancel the interferences from the secondary users to the primary receiver, the interferences from the primary transmitter to the secondary users, and the inter-secondary-user interferences, in order to guarantee the communication quality of both the primary and secondary users. Based on the zero-forcing method, the transceivers are designed to minimize the noise power amplified by the relays. It is shown that the proposed transceiver design algorithm outperform the existed algorithm.
Mortality and cost of acute and chronic kidney disease after cardiac surgery

Purpose of review Acute and chronic kidney diseases (AKI and CKD) have far-reaching implications for surgical patients in regards to postoperative outcomes and hospital cost. We review the recent literature on the effects of AKI and CKD on morbidity, mortality, and resource utilization among cardiac surgery patients. Recent findings Both AKI and CKD increase the risk for short-term and long-term mortalities, morbidity, length of stay, and hospital cost among postoperative patients, with increasing disease stage correlating with worse outcomes. Even the mildest forms of AKI (RIFLE-R) and CKD (proteinuria without an observed reduction in estimated glomerular filtration rate) demonstrate worse clinical outcomes compared with patients with no AKI or CKD. Outcomes are worse even in patients who achieve full renal recovery before hospital discharge. These complications dramatically increase ICU length of stay, hospital length of stay, resource utilization, and both in-hospital and postdischarge costs, as evidenced by lower rates of discharges to home. Summary AKI and CKD remain prevalent, morbid, and costly conditions for cardiac surgery patients. Better risk stratification, early diagnosis, and earlier interventions are needed to prevent the consequences of these diseases.
The square root Unscented Kalman Filter in spacecrafts autonomous navigation

Concerning the problems in the process of the spacecraftpsilas autonomous navigation, the square-root unscented Kalman filter(SRUKF) is designed to estimate the relative state between the pursuing spacecraft and the target. C-W equation is discreted to iterate. For the case that all the measuring datas get from radars, the observing equation was deduced. Compared with the conventional extended Kalman filter(EKF), no Jacobian matrix is required to calculate in this algorithm, the computational cost is reduced and the estimation accuracy is also improved. Simulation results show that the algorithm can quickly converge even for large initial errors and is efficient.
Improved Iterative Detection and Achieved Throughputs of Multiband OFDM Systems Under Imperfect Channel Estimation

Assuming imperfect channel estimation, we propose an impro ved detector for ultra wideband (UWB) systems employing multiband orthogonal frequency-di vision multiplexing (MB-OFDM). By adopting a Bayesian approach involving the statistics of th e c annel estimation errors, we formulate an improved maximum-likelihood (ML) detection metric taki ng into account the characteristics of the channel estimates. As a first step, we propose a modified it erative detector based on maximum a posteriori which reduces the impact of channel uncertainty on the decod er performance, by an appropriate use of this metric. The results are compared to t hose obtained by using a detector based on a mismatched ML metric, which uses the channel estimate as if it was the perfect channel. In a second step, we calculate the information rates achieved by both th e improved and mismatched ML detectors, in terms of achievable outage rates. These outage rates are com pared to those provided by a theoretical (not practical) decoder defined as the best decoder in the presenc e of channel estimation errors. Numerical results over both uncorrelated Rayleigh fading channels an d realistic UWB channels show that the improved detector provides significant gains in terms of bit error rate and achievable outage rates, compared to the classically-used mismatched approach, wit out any increase in the receiver complexity. I. I NTRODUCTION Multiband orthogonal frequency-division multiplexing (M B-OFDM) is a spectrally efficient technique proposed for high data-rate, short-range ultra w ideband (UWB) applications operating in the range from 3.1 to 10.6 GHz [1]. In this scheme, the avail ble 7.5 GHz of UWB spectrum is divided into several subbands of at least 500 MHz bandwidt h, with a conventional OFDM modulation within each subband. The material in this paper was published in part at the 40-th Asilomar Conference on Signals, Systems, and Computers. August 25, 2007 DRAFT
Improving Automatic Sentence Boundary Detection with Confusion Networks

We extend existing methods for automatic sentence boundary detection by leveraging multiple recognizer hypotheses in order to provide robustness to speech recognition errors. For each hypothesized word sequence, an HMM is used to estimate the posterior probability of a sentence boundary at each word boundary. The hypotheses are combined using confusion networks to determine the overall most likely events. Experiments show improved detection of sentences for conversational telephone speech, though results are mixed for broadcast news.