Miracle-dz/UniFAR-FTUs huggingface dataset:
The emerging role of consolidation and maintenance therapy for transplant-eligible multiple myeloma patients

Multiple myeloma (MM) is an incurable malignant cancer of plasma cell origin. It is highly treatable with glucocorticoids, alkylating drugs, and novel agents including the proteasome inhibitors (bortezomib and carfilzomib) and the immunomodulatory drugs (IMiDs) thalidomide, lenalidomide and pomalidomide. Induction regimens incorporating the newer agents have resulted in deeper responses that have translated into prolonged response and survival for transplant eligible and transplant-ineligible MM patients. For the transplant-eligible patient, the current approach to those patients requiring therapy is induction, hematopoietic stem cell (HSC) collection, autologous HSC transplant (AHSCT) which may be followed by consolidation. Maintenance therapies with bortezomib or lenalidomide prolong response and appear to improve overall survival. For very high risk patients, allogeneic (alloHSCT) is an alternative therapy that may improve survival for selected patients. Incorporation of new therapies in combination with existing agents should lead increased response and improved survival of the MM patient with the ultimate goal of development of curative approaches for this disease.
Blonanserin Augmentation of Atypical Antipsychotics in Patients with Schizophrenia-Who Benefits from Blonanserin Augmentation?: An Open-Label, Prospective, Multicenter Study

Objective The purpose of this study was to investigate the efficacy and tolerability of atypical antipsychotics (AAPs) with augmentation by blonanserin in schizophrenic patients. Methods aA total of 100 patients with schizophrenia who were partially or completely unresponsive to treatment with an AAP were recruited in this 12-week, open-label, non-comparative, multicenter study. Blonanserin was added to their existing AAP regimen, which was maintained during the study period. Efficacy was primarily evaluated using the Positive and Negative Syndrome Scale (PANSS) at baseline and at weeks 2, 4, 8, and 12. Predictors for PANSS response (≥20% reduction) were investigated. Results The PANSS total score was significantly decreased at 12 weeks of blonanserin augmentation (-21.0±18.1, F=105.849, p<0.001). Moreover, 51.0% of participants experienced a response at week 12. Premature discontinuation of blonanserin occurred in 17 patients (17.0%); 4 of these patients dropped out due to adverse events. The patients who benefited the most from blonanserin were those with severe symptoms despite a treatment with a higher dose of AAP. Conclusion Blonanserin augmentation could be an effective strategy for patients with schizophrenia who were partially or completely unresponsive to treatment with an AAP.
Evidential seed-based semi-supervised clustering

Evidential clustering algorithms produce credal partitions that enhance the concepts of hard, fuzzy or possibilistic partitions to represent all assignments ranging from complete ignorance to total certainty. This paper introduces the first semi-supervised extension of the evidential c-means clustering algorithm that can benefit from the introduction of a small set of labeled data (or seeds). Experiments conducted on real datasets show that the introduction of seeds can lead to a significant increase in clustering accuracy compared to a traditional evidential clustering algorithm as well as a decrease in the number of iterations to convergence.
Bone metabolism and mineral density following renal transplantation

AIM To study bone turnover following renal transplantation using a panel of biochemical markers and to correlate the results with both areal and volumetric bone mineral density (BMD). PATIENTS A total of 31 patients aged 18.1 years were transplanted 5.4 years before this study. Control patients (n = 31) were age and gender matched. METHODS In addition to measurement of biochemical markers, BMD was measured by single photon absorptiometry and peripheral quantitative computed tomography on the non-dominant radius. RESULTS Patients had reduced glomerular filtration rate, raised concentrations of serum phosphate, serum procollagene type I carboxy terminal propeptide, osteocalcin, and serum procollagene type I cross linked carboxy terminal telopeptide. The differences were still significant if only patients with normal intact parathyroid hormone were considered. BMD single photon absorptiometry Z score for age was significantly decreased. Following standardisation for height the differences were no longer present. With volumetric techniques patients had normal trabecular but decreased cortical and total BMD compared to age matched controls, but there was no difference from height matched controls. CONCLUSION Markers of bone turnover are increased following renal transplantation. However, the biochemical analysis did not allow conclusions to be drawn on the bone mineral content. BMD single photon absorptiometry Z score corrected for height and BMD measured by quantitative computed tomography compared to height matched controls were normal in paediatric renal transplantation patients. Height matched controls should be used in both areal and volumetric BMD measurements in states of growth failure.
Study of Driver Assistant Services using Ubiquitous Smartphone

Smartphones are increasingly becoming popular. All Smartphones have rich set of sensors, which can be used to provide driver assistant services. Services such as road traffic information and road condition to provide such services, there is need of sensors such as GPS, Gyroscope, Accelerometer. Now day’s smartphones are coming with this sensor. Smartphone camera sensor, one of the most powerful and neglected Sensor can be used to analyses traffic scene. In this paper we have provided surveys on different approaches to provide collaborative driver assistant service and analyze road surface disruption.
TRIBLER: a social‐based peer‐to‐peer system

Most current peer‐to‐peer (P2P) file‐sharing systems treat their users as anonymous, unrelated entities, and completely disregard any social relationships between them. However, social phenomena such as friendship and the existence of communities of users with similar tastes or interests may well be exploited in such systems in order to increase their usability and performance. In this paper we present a novel social‐based P2P file‐sharing paradigm that exploits social phenomena by maintaining social networks and using these in content discovery, content recommendation, and downloading. Based on this paradigm's main concepts such as taste buddies and friends, we have designed and implemented the TRIBLER P2P file‐sharing system as a set of extensions to BitTorrent. We present and discuss the design of TRIBLER, and we show evidence that TRIBLER enables fast content discovery and recommendation at a low additional overhead, and a significant improvement in download performance. Copyright © 2007 John Wiley & Sons, Ltd.
Real time monitoring of moment magnitude by waveform inversion

An instantaneous measure of the moment magnitude (Mw) of an ongoing earthquake is estimated from the moment rate function (MRF) determined in real‐time from available seismic data using waveform inversion. Integration of the MRF gives the moment function from which an instantaneousMw is derived. By repeating the inversion procedure at regular intervals while seismic data are coming in we can monitor the evolution of seismic moment and Mw with time. The final size and duration of a strong earthquake can be obtained within 12 to 15 minutes after the origin time. We show examples of Mw monitoring for three large earthquakes at regional distances. The estimated Mw is only weakly sensitive to changes in the assumed source parameters. Depending on the availability of seismic stations close to the epicenter, a rapid estimation of the Mw as a prerequisite for the assessment of earthquake damage potential appears to be feasible.
A resource management strategy for interconnected WLAN and UMTS networks based on user mobility, call renegotiation, and call reallocation

The users of telecommunications services are demanding access to their subscribed services in mobile contexts. This demand leads to the development of mechanisms that enable the transference of service sessions between networks, seamlessly to the user. These mechanisms allow the operator to jointly manage its networks resources, providing a better service to its customers and, simultaneously, increasing its revenue. Starting from the UMTS and WLAN interconnection architecture defined by 3GPP, this paper presents a new strategy for joint radio resource management, suitable for contexts where these networks are interconnected. This strategy bases its decisions on criteria related to user mobility characteristics. The algorithm also introduces the possibility of renegotiating new calls and reallocating running calls from one access network to another. The new radio resource management strategy is compared with two well-known strategies, the former based on coverage area and the later based on load balancing. The comparison studies show the proposed strategy outperforms the other strategies in what concerns call blocking probability and applications QoS support. Besides, the proposed strategy tends to reduce the handoffs between networks.
Transcriptome Analysis Reveals that Red and Blue Light Regulate Growth and Phytohormone Metabolism in Norway Spruce [Picea abies (L.) Karst.]

The mechanisms by which different light spectra regulate plant shoot elongation vary, and phytohormones respond differently to such spectrum-associated regulatory effects. Light supplementation can effectively control seedling growth in Norway spruce. However, knowledge of the effective spectrum for promoting growth and phytohormone metabolism in this species is lacking. In this study, 3-year-old Norway spruce clones were illuminated for 12 h after sunset under blue or red light-emitting diode (LED) light for 90 d, and stem increments and other growth traits were determined. Endogenous hormone levels and transcriptome differences in the current needles were assessed to identify genes related to the red and blue light regulatory responses. The results showed that the stem increment and gibberellin (GA) levels of the seedlings illuminated by red light were 8.6% and 29.0% higher, respectively, than those of the seedlings illuminated by blue light. The indoleacetic acid (IAA) level of the seedlings illuminated by red light was 54.6% lower than that of the seedlings illuminated by blue light, and there were no significant differences in abscisic acid (ABA) or zeatin riboside [ZR] between the two groups of seedlings. The transcriptome results revealed 58,736,166 and 60,555,192 clean reads for the blue-light- and red-light-illuminated samples, respectively. Illumina sequencing revealed 21,923 unigenes, and 2744 (approximately 93.8%) out of 2926 differentially expressed genes (DEGs) were found to be upregulated under blue light. The main KEGG classifications of the DEGs were metabolic pathway (29%), biosynthesis of secondary metabolites (20.49%) and hormone signal transduction (8.39%). With regard to hormone signal transduction, AUXIN-RESISTANT1 (AUX1), AUX/IAA genes, auxin-inducible genes, and early auxin-responsive genes [(auxin response factor (ARF) and small auxin-up RNA (SAUR)] were all upregulated under blue light compared with red light, which might have yielded the higher IAA level. DELLA and phytochrome-interacting factor 3 (PIF3), involved in negative GA signaling, were also upregulated under blue light, which may be related to the lower GA level. Light quality also affects endogenous hormones by influencing secondary metabolism. Blue light promoted phenylpropanoid biosynthesis, phenylalanine metabolism, flavonoid biosynthesis and flavone and flavonol biosynthesis, accompanied by upregulation of most of the genes in their pathways. In conclusion, red light may promote stem growth by regulating biosynthesis of GAs, and blue light may promote flavonoid, lignin, phenylpropanoid and some hormones (such as jasmonic acid) which were related to plant defense in Norway spruce, which might reduce the primary metabolites available for plant growth.
Knowledge-based methods for classifier combination: an experimental investigation

Many combination methods have been proposed so far for classifier combination. In order to achieve better performance, some methods also use a-priori knowledge on the set of classifiers. Unfortunately, in this case the effectiveness of the methods is very difficult to predict since there is little assurance that the results obtained in controlled tests can be obtained under different working conditions imposed by the real applications. In this paper, the role of a-priori knowledge in classifier combination is evaluated. A recent methodology is used for the analysis of methods for classifier combination. The performance of a combination method is measured under different working conditions by simulating sets of classifiers with different characteristics for the test. A random variable is used to simulate each classifier while a suitable estimator of stochastic correlation is used to measure the agreement among classifiers.
Mean version space: a new active learning method for content-based image retrieval

In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed up the convergence to the query concept, several active learning methods have been proposed instead of random sampling to select images for labeling by the user. In this paper, we propose a novel active learning method named mean version space, aiming to select the optimal image in each round of relevance feedback. Firstly, by diving into the lemma that motivates support vector machine active learning method (SVM<i><inf>active</inf></i>), we come up with a new criterion which is tailored for each specific learning task and will lead to the fastest shrinkage of the version space in all cases. The criterion takes both the size of the version space and the posterior probabilities into consideration, while existing methods are only based on one of them. Moreover, although our criterion is designed for SVM, it can be justified in a general framework. Secondly, to reduce processing time, we design two schemes to construct a small candidate set and evaluate the criterion for images in the set instead of all the unlabeled images. Systematic experimental results demonstrate the superiority of our method over existing active learning methods
New Results for Learning Noisy Parities and Halfspaces

We address well-studied problems concerning the learn-ability of parities and halfspaces in the presence of classification noise. Learning of parities under the uniform distribution with random classification noise, also called the noisy parity problem is a famous open problem in computational learning. We reduce a number of basic problems regarding learning under the uniform distribution to learning of noisy parities. We show that under the uniform distribution, learning parities with adversarial classification noise reduces to learning parities with random classification noise. Together with the parity learning algorithm of Blum et al. (2003), this gives the first nontrivial algorithm for learning parities with adversarial noise. We show that learning of DNF expressions reduces to learning noisy parities of just logarithmic number of variables. We show that learning of k-juntas reduces to learning noisy parities of k variables. These reductions work even in the presence of random classification noise in the original DNF or junta. We then consider the problem of learning halfspaces over Qopfn with adversarial noise or finding a halfspace that maximizes the agreement rate with a given set of examples. We prove an essentially optimal hardness factor of 2 - epsi, improving the factor of (85/84) - epsi due to Bshouty and Burroughs (2002). Finally, we show that majorities of halfspaces are hard to PAC-learn using any representation, based on the cryptographic assumption underlying the Ajtai-Dwork cryptosystem
Geometric Calibration of a Micro-CT System and Performance for Insect Imaging

Micro-CT with a high spatial resolution in combination with computer-based-reconstruction techniques is considered a powerful tool for morphological study of insects. The quality of CT images crucially depends on the precise knowledge of the scan geometry of the micro-CT system. In this paper, we have proposed a method to calculate the deviation of rotating axis for compensating deficiency of existing methods. A practical application of this geometric calibration method of the micro-CT system for insect imaging is presented. We have performed the computer-simulation study and experimental study with our prototype micro-CT system. The results demonstrate that the proposed technique is accurate and robust. In addition, we have evaluated the imaging characteristics of the detector in terms of modulation-transfer function (MTF). Finally, insect imaging performance and image reconstruction from data acquired with different energies are presented.
An assertional correctness proof of a self-stabilizing /spl lscr/-exclusion algorithm

A formal correctness proof of a self-stabilizing lscr-exclusion algorithm (SLEX) is described. The analyzed algorithm is an improvement of the SLEX due to Abraham, Dolev, Herman, and Koll, since our version satisfies a stronger liveness property. The proof is formulated in linear-time temporal logic and utilizes a history variable to model access to regular registers. The proof consists of a safety part and a liveness part. Our analysis provides some new insight in the correctness of the algorithm: (1) our proof is constructive. That is, we explicitly formulate auxiliary quantities required to establish some of the properties. This contrasts with the operational arguments of Abraham et al., where many quantities are not explicitly formulated and the validity of the above mentioned properties are established by disproving their non-existence. (2) We characterize processes (and their minimum number) identified by some process as attempting to enter the critical section. (3) A novel proof rule for reasoning about programs in the presence of disabled processes is presented to structure the liveness proof
Climatic Condition and Synoptic Regimes of Two Intense Snowfall Events in Eastern China and Implications for Climate Variability

This study investigates the climatic condition and synoptic regimes of two intense snowfall events (ISEs) in central eastern China (CEC) during January 2018, focusing on the mechanisms of northerly cold advection and southerly water vapor transport. The northerly cold advections invading CEC were associated with a strengthened Siberian High, which could be partially attributed to an influence of reduced sea ice in the Kara Sea‐Barents Sea during November 2017 to January 2018 on a reduced meridional temperature gradient between the midlatitudinal Eurasia and Arctic regions. The southerly water vapor transport contributing to ISEs was associated with a zonal dipole pattern in the atmosphere, which was characterized by an anomalous anticyclone over the western North Pacific and an anomalous low over the Tibetan Plateau and India. The La Niña condition provided a climatic condition for an anomalous anticyclone persisting over the western North Pacific during January 2018, which was influenced by a strengthened convection over the western tropical Pacific and influenced by the air‐sea interaction over the central‐northern Pacific. The anomalous low over the Tibetan Plateau and India was associated with active eastward propagating synoptic‐scale waves originating from the midlatitudinal North Atlantic. The implication of aforementioned climatic conditions on climate variability was further discussed. Our results suggest that a reduced sea ice in the Kara Sea during the preceding late autumn and a concurrent La Niña‐like condition may contribute to an increased frequency of ISEs in CEC during winter on the interannual time scale.
A real-time high dynamic range HD video camera

Standard cameras suffer from low video quality in high dynamic range scenes. In such scenes, parts of the video are either too dark or too bright. This is because lighting is very unevenly distributed in a high dynamic range scene. A standard camera, which typically has a 10 or 12 bit sensor, cannot capture the information both in dark and bright regions with one exposure. High dynamic range (HDR) imaging addresses this problem by fusing information from multiple exposures and rendering a dynamic range compressed result, which is also called dynamic range enhancement (DRE) or tone mapping. DRE is a challenging problem because human perception of brightness/contrast is quite complex and is highly dependent on image content. We present an embedded real-time HDR video camera system that provides 30fps, 720p/1080p high dynamic range video.
Topic-oriented query expansion for web search

The contribution of this paper includes three folders: (1) To introduce a topic-oriented query expansion model based on the Information Bottleneck theory that classify terms into distinct topical clusters in order to find out candidate terms for the query expansion. (2) To define a term-term similarity matrix that is available to improve the term ambiguous problem. (3) To propose two measures, intracluster and intercluster similarities, that are based on proximity between the topics represented by two clusters in order to evaluate the retrieval effectiveness. Results of several evaluation experiments in Web search exhibit the average intracluster similarity was improved for the gain of 79.1% while the average intercluster similarity was decreased for the loss of 36.0%.
Stream Health Evaluation Using a Combined Approach of Multi-Metric Chemical Pollution and Biological Integrity Models

Bouchung Stream is a large tributary of the Geum River watershed that is simultaneously affected by wastewater treatment plant effluents and agricultural activities in the watershed area. The focal subject was to diagnose the chemical and biological health of the temperate stream by using a combined approach of the multi-metric water pollution index (WPI) and the index of biological integrity (IBIKR), using datasets from 2008–2014. Water chemistry analyses indicated seasonal and inter-annual variations mainly linked to the intensity of monsoon rainfall in the watershed, potentially causing the availability of agricultural runoff water. The main events of phosphorus inflow and nitrogen dilutions occurred during July–August. Temporal and spatial heterogeneities were observed and were largely recognizable due to nutrient enrichment and organic matter intensification. Chlorophyll showed weak linear relation to total phosphorus (R2 = 0.17) but no relation to total nitrogen (p > 0.05). Fish compositions analyzed as trophic/tolerance guilds in relation to water chemistry showed visible decline and modifications. Average WPI site scores ranged from 33–23, indicating an excellent upstream to fair downstream water quality status. Correspondingly, IBIKR scores ranged between 38–28 approximating with WPI site classification, as well as both indices showed higher regression relation (R2 = 0.90). Fish guild analyses revealed tolerant and omnivore species dominating the downstream, while sensitive and insectivores depleting in approximation with changing water chemistry and was confirmed by the principal component analysis. In addition, the fish guilds meticulously responded to phosphorus inflows. In conclusion, overall stream health and water chemistry analyses indicated continuous chemical and biological degradation influencing the trophic and tolerance fish guilds. Moreover, the combined application approach of WPI and IBIKR could help in better understanding the chemical and biological mechanisms in rivers and streams.