Miracle-dz/UniFAR-FTUs huggingface dataset:
SGLT2 Inhibitors: A New Emerging Therapeutic Class in the Treatment of Type 2 Diabetes Mellitus

The incidence of type 2 diabetes mellitus is increasing worldwide. The existing therapeutic classes of antidiabetic drugs are not adequately effective in maintaining long‐term glycemic control in most patients, even when used in combination. One emerging novel therapeutic class of antidiabetic drugs is sodium glucose cotransporter 2 (SGLT2) inhibitors. SGLT2 accounts for 90% of the glucose reabsorption in the kidney. The SGLT2 inhibitors increase urinary excretion of glucose and lower plasma glucose levels in an insulin‐independent manner. Dapagliflozin, the most prominent molecule in this class, is currently in a phase III clinical trial. Other members of this class (eg, sergliflozin, remogliflozin) are also in different phases of clinical trials. This class of novel agents can effectively control blood sugar level without producing weight gain or hypoglycemia. Results of ongoing phase III clinical trials are crucial to determine whether the risk‐benefit ratio will allow approval of this new class of drugs for the management of type 2 diabetes mellitus.
Media consumption and the future of public connection

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Fuzzy entropy based nonnegative matrix factorization for muscle synergy extraction

The concept of muscle synergies has proven to be an effective method for representing patterns of muscle activation. The number of degrees of freedom to be controlled are reduced while also providing a flexible platform for producing detailed movements using synergies as building blocks. It has previously been shown that small components of movement are crucial to producing precise and coordinated movement. Methods which focus on the variance of the data make it possible to overlook these small components in the synergy extraction process. However, algorithms which address the inherent complexity in the neuromuscular system are lacking. To that end we propose a new nonnegative matrix factorization algorithm which employs a cross fuzzy entropy similarity measure, thus, extracting muscle synergies which preserve the complexity of the recorded muscular data. The performance of the proposed algorithm is illustrated on representative EMG data.
A Natural Language Processing Infrastructure for Turkish

We built an open-source software platform intended to serve as a common infrastructure that can be of use in the development of new applications involving the processing of Turkish. The platform incorporates a lexicon, a morphological analyzer/generator, and a DCG parser/generator that translates Turkish sentences to predicate logic formulas, and a knowledge base framework. Several developers have already utilized the platform for a variety of applications, including conversation programs and an artificial personal assistant, tools for automatic analysis of rhyme and meter in Turkish folk poems, a prototype sentence-level translator between Albanian, Turkish, and English, natural language interfaces for generating SQL queries and JAVA code, as well as a text tagger used for collecting statistics about Turkish morpheme order for a speech recognition algorithm. The results indicate the adaptability of the infrastructure to different kinds of applications and how it facilitates improvements and modifications.
Consumer Stockpiling and Price Competition in Differentiated Markets

In many storable-goods markets, firms are often aware that consumers may strategically adjust purchase timing in response to expected price dynamics. For example, in periods when prices are low, consumers stockpile for future consumption. This paper investigates the dynamic impact of consumer stockpiling on competing firms' strategic pricing decisions in differentiated markets. The necessity of equilibrium consumer storage for storable products is re-examined. It is shown that preference heterogeneity generates differential consumer stockpiling propensity, thereby intensifying future price competition. As a result, consumer storage may not necessarily arise as an equilibrium outcome. Economic forces are also investigated that may mitigate the competition-intensifying effect of consumer inventories and that, hence, may lead to equilibrium consumer storage.
Technical Reports on Mathematical and Computing Sciences: TR-CXXX title: Algorithmic Aspects of Boosting

We discuss algorithmic aspects of boosting techniques, such as Majority Vote Boosting [Fre95], AdaBoost [FS97], and MadaBoost [DW00a]. Considering a situation where we are given a huge amount of examples and asked to find some rule for explaining these example data, we show some reasonable algorithmic approaches for dealing with such a huge dataset by boosting techniques. Through this example, we explain how to use and how to implement “adaptivity” for scaling-up existing algorithms.
The Challenges of No Child Left Behind: Understanding the Issues of Excellence, Accountability, and Choice

Chapter 1 Introduction Chapter 2 Changing Accountability Measures and Achievement Chapter 3 Adequate Yearly Progress (AYP) Chapter 4 Highly-Qualified Teachers Chapter 5 Title I: Overview Chapter 6 Title I: Reading and Early Childhood Chapter 7 NCLB and School Reform: Charters and Vouchers Chapter 8 Restructuring Chapter 9 Impact of NCLB on School Finance Chapter 10 High School Reform and Other Future Trends
Discussion—Security Analyst Experience and Post-Earnings-Announcement Drift

Mikhail, Walther, and Willis (2003a) (hereafter MWW) show that the postearnings-announcement drift (PEAD) is less for firms followed by more experienced analysts. They motivate their study by noting that prior studies (e.g., Bernard and Thomas [1990]) show that PEAD is due to the market’s failure to properly incorporate in security prices serial correlation in seasonally differenced quarterly earnings. Furthermore, analysts fail to properly incorporate in their forecasts serial correlation in forecast errors (e.g., Ali et al. [1992]; Abarbanell and Bernard [ 19921). However, with experience, they become better at it (Mikhail, Walther and Willis 2003). Also, as analysts’ experience increases, the market’s expectations tend to become more consistent with analysts’ forecasts than with seasonal random walk forecasts (Mikhail, Walther, and Willis [ 19971). Based on these prior findings, MWW predict that the amount of PEAD would be smaller for firms followed by more experienced analysts because the serial correlation in their forecast errors is likely to be smaller and the market is more likely to use analysts’ forecasts rather than seasonal random walk forecasts in forming their expectations. My discussion of MWW is organized as follows. The first section discusses the contribution MWW makes to the literature on the post earnings announcement drift phenomenon. The second section comments on their research design. The final section discusses opportunities for future research.
Swimming Training Induces Liver Mitochondrial Adaptations to Oxidative Stress in Rats Submitted to Repeated Exhaustive Swimming Bouts

Background and Aims Although acute exhaustive exercise is known to increase liver reactive oxygen species (ROS) production and aerobic training has shown to improve the antioxidant status in the liver, little is known about mitochondria adaptations to aerobic training. The main objective of this study was to investigate the effects of the aerobic training on oxidative stress markers and antioxidant defense in liver mitochondria both after training and in response to three repeated exhaustive swimming bouts. Methods Wistar rats were divided into training (n = 14) and control (n = 14) groups. Training group performed a 6-week swimming training protocol. Subsets of training (n = 7) and control (n = 7) rats performed 3 repeated exhaustive swimming bouts with 72 h rest in between. Oxidative stress biomarkers, antioxidant activity, and mitochondria functionality were assessed. Results Trained group showed increased reduced glutathione (GSH) content and reduced/oxidized (GSH/GSSG) ratio, higher superoxide dismutase (MnSOD) activity, and decreased lipid peroxidation in liver mitochondria. Aerobic training protected against exhaustive swimming ROS production herein characterized by decreased oxidative stress markers, higher antioxidant defenses, and increases in methyl-tetrazolium reduction and membrane potential. Trained group also presented higher time to exhaustion compared to control group. Conclusions Swimming training induced positive adaptations in liver mitochondria of rats. Increased antioxidant defense after training coped well with exercise-produced ROS and liver mitochondria were less affected by exhaustive exercise. Therefore, liver mitochondria also adapt to exercise-induced ROS and may play an important role in exercise performance.
On Subliminal Channels in Encrypt-on-Cast Voting Systems

Ballot secrecy, while essential, is difficult to achieve with any voting system cryptographic or otherwise. Moreover, the majority of cryptographic voting systems introduce new ballot secrecy problems. In encrypt-on-cast voting systems, like that of Benaloh [1, 2], a malicious voting machine can use the encrypted votes that it posts to the public bulletin board as a subliminal channel to convey information about voters' choices to a coercer. Although it was known that a machine could manipulate the randomness used to encrypt the votes to leak information [14], we show that this threat is more severe than previously recognized and that existing mitigations may be ineffective. A compromised machine may only need to leak a few bits and modify only a handful of ballots in order to coerce most of the voters in a polling place. In light of this threat, we propose an extension to the Benaloh scheme that allows anyone to verify that every ciphertext on the bulletin board uses the right randomness. Finally, we show that even without manipulating the randomness, a machine can still use the ciphertexts to leak a small, but potentially dangerous, number of bits by strategically flipping a few votes. Overall, we show that while subliminal channels in encrypt-on-cast voting systems can be partially mitigated, they cannot yet be eliminated completely.
Outage analysis in a cooperative system with beamforming and worst relay cancellation

In this paper, a system that provides transmission over relays utilizing decode&forward (DF) transmission protocol is considered and beamforming, worst relay cancellation criteria that maximize the diversity of the system are applied. Bit error rate (BER) of this system is examined under chosen criteria; as a result, it is observed that full diversity order can be reached as the channel between the source and the relays improves. Furthermore, outage probability upper bound for the system utilizing both relay cancellation and beamforming is analyzed. Making use of this upper bound, the diversity order that is observed from the BER curves is validated. Simulations are carried out for various numbers of relays and differential signal to noise ratio (DSNR) values.
Synchronized Phasor Measurements Based Power System Dynamic State Estimation

 Abstract— The dynamic state estimation (DSE) applied to power systems with synchrophasor measurements would estimate the system's true state based on measurements and predictions. In this application, as phasor measurement units (PMUs) are not deployed at all power system buses; state predictions would enhance the redundancy of DSE input data. The importance of predicted and measured data in DSE is affected by their confidence levels, which are inversely proportional to the corresponding variances. In practical cases, power system states may undergo drastic changes during hourly load fluctuations, component outages, or network switching's. In such conditions, the inclusion of predicted values could degrade the power system state estimation. The proposed model accommodates system wide synchronized measurements of PMUs, which could be of interest to smart grid applications in energy management systems. In this paper phasor measurement unit (PMU's) is modelled in Simulink in MATLAB. In this paper, a new state estimation method based on the extended weighted least squares (WLS) method and Newton Raphson state estimation employing Jacobin matrix for considering both measurement errors and model inaccuracy. Simulation studies are conducted on an illustrative IEEE three-bus system based on measurement values obtained by PMU'S.
On Scalability, Generalization, and Hybridization of Coevolutionary Learning: A Case Study for Othello

This study investigates different methods of learning to play the game of Othello. The main questions posed concern scalability of algorithms with respect to the search space size and their capability to generalize and produce players that fare well against various opponents. The considered algorithms represent strategies as n-tuple networks, and employ self-play temporal difference learning (TDL), evolutionary learning (EL) and coevolutionary learning (CEL), and hybrids thereof. To assess the performance, three different measures are used: score against an a priori given opponent (a fixed heuristic strategy), against opponents trained by other methods (round-robin tournament), and against the top-ranked players from the online Othello League. We demonstrate that although evolutionary-based methods yield players that fare best against a fixed heuristic player, it is the coevolutionary temporal difference learning (CTDL), a hybrid of coevolution and TDL, that generalizes better and proves superior when confronted with a pool of previously unseen opponents. Moreover, CTDL scales well with the size of representation, attaining better results for larger n-tuple networks. By showing that a strategy learned in this way wins against the top entries from the Othello League, we conclude that it is one of the best 1-ply Othello players obtained to date without explicit use of human knowledge.
A Probabilistic Kernel for Splice Site Prediction

One of the most important tasks in correctly annotating genes in higher organism is to accurately locate the DNA splice sites. Although relatively high accuracy has been achieved by the existing methods, most of these prediction methods are computationally very expensive. Considering the enormousness of DNA sequences, the computing speed is an important issue. In this paper, we propose to use a probabilistic kernel-based method to predict DNA splice sites, which project the sequence data into a new probabilistic feature space. We then use Support Vector Machines to recognize the true splice sites. While the performance is comparable to the results obtained with polynomial kernels, the computation is performed much faster.
Initiation of Apoptosis versus Necrosis by Photodynamic Therapy with Chloroaluminum Phthalocyanine

Abstract— While chloroaluminum phthalocyanine is a highly effective photosensitizer of murine leukemia P388 or L1210 cells, the mode of cell death varies as a function of the PDT dose. When cells were incubated with 0.3 mUM of the sensitizer, a light dose of 45 mJ cm‐2 (670 5 nm) yielded a 90% apoptotic cell population within 60 min. The sensitizer localized throughout the cytoplasm and catalyzed both lysosomal and mitochondrial photodamage at this light dose. Higher light doses yielded progressively more membrane photodamage and inhibited the apoptotic response as determined by the examination of Hochst dye HO 33342‐IabeIed nuclei, DNA fragmentation on gels and a poly(adenosylribose) polymerase (PARP)‐cleavage assay. Pulse‐field gel electrophoresis revealed nonspecific DNA degradation to particles 50 kbp at the higher PDT doses but neither PARP cleavage nor apoptotic nuclei
Reflects Body Mechanics in Human Locomotion Migration of Motor Pool Activity in the Spinal Cord

[PDF] [Full Text] [Abstract] , April , 2011; 105 (4): 1429-1431. J Neurophysiol Enrico Chiovetto -motoneuron pools during locomotion α activity of the The motor system plays the violin: a musical metaphor inferred from the oscillatory [PDF] [Full Text] [Abstract] , September , 2011; 106 (3): 1525-1536. J Neurophysiol Lacquaniti Francesca Sylos Labini, Yuri P. Ivanenko, Germana Cappellini, Silvio Gravano and Francesco Smooth changes in the EMG patterns during gait transitions under body weight unloading [PDF] [Full Text] [Abstract] , October , 2011; 106 (4): 1943-1953. J Neurophysiol Nicholas AuYong, Karen Ollivier-Lanvin and Michel A. Lemay air-stepping in adult spinal cats Population spatiotemporal dynamics of spinal intermediate zone interneurons during
THE INFLUENCE OF THE SUPRARENAL GLAND ON THE THYMUS

1. Regeneration of involuted thymuses of old rats follows double suprarenalectomy in this species with great constancy. 2. Partial thymectomy alone does not induce compensatory secondary hyperplasia in involuting glands. 3. Regeneration of the thymus following suprarenalectomy would appear to be completed in most rats in about 2 weeks; and it probably begins in the medulla.
HCO+ emission excess in bipolar outflows

A plausible model is proposed for the enhancement of the abundance of molecular species in bipolar outflow sources. In this model, levels of HCO + enhancement are considered based on previous chemical calculations, which are assumed to result from shock-induced desorption and photoprocessing of dust grain ice mantles in the boundary layer between the outflow jet and the surrounding envelope. A radiative transfer simulation that incorporates chemical variations within the flow shows that the proposed abundance enhancements in the boundary layer are capable of reproducing the observed characteristics of the outflow seen in HCO + emission in the star-forming core L1527. The radiative transfer simulation also shows that the emission lines from the enhanced molecular species, which trace the boundary layer of the outflow, exhibit complex line profiles, indicating that detailed spatial maps of the line profiles are essential in any attempt to identify the kinematics of potential infall/outflow sources. This study is one of the first applications of a full three-dimensional radiative transfer code which incorporates chemical variations within the source.
Astrobiological signatures: prospects for the detection of non-terrestrial biological material

The possibilities for detecting non-terrestrial biological material are briefly reviewed in light of the flurry of extrasolar planet detections over the last ten years and the forthcoming space missions designed to search for signs of extraterrestrial life. We summarize the evidence for non-terrestrial organic material and the challenges involved in the development of robust and reliable biosignatures, i.e. features whose presence requires a biological origin. It is necessary to distinguish between prebiotic material, which is likely to be a necessary precursor to life but which is not produced by a biological system, and the detection of either biological material itself or its effect on the environment. We discuss the use of chirality and spectrally resolved circular polarization as a remote-sensing technique for distinguishing between biological and non-biological substances.
Base change and a problem of Serre

We establish a version of “level-lowering” for mod p Galois representations arising from the reductions of representations associated to Hilbert modular forms. In particular, we show that level-lowering can be easily achieved if one replaces the base field with a suitable solvable extension. This is often enough for applications to proving the modularity of p-adic representations.
Highly nonrepetitive sequences: Winning strategies from the local lemma

We prove game‐theoretic versions of several classical results on nonrepetitive sequences, showing the existence of winning strategies using an extension of the Lovász Local Lemma which can dramatically reduce the number of edges needed in a dependency graph when there is an ordering underlying the significant dependencies of events. This appears to represent the first successful application of a Local Lemma to games. © 2010 Wiley Periodicals, Inc. Random Struct. Alg. , 2011
Improving bag-of-features action recognition with non-local cues

Local space-time features have recently shown promising results within Bag-of-Features (BoF) approach to action recognition in video. Pure local features and descriptors, however, provide only limited discriminative power implying ambiguity among features and sub-optimal classification performance. In this work, we propose to disambiguate local space-time features and to improve action recognition by integrating additional nonlocal cues with BoF representation. For this purpose, we decompose video into region classes and augment local features with corresponding region-class labels. In particular, we investigate unsupervised and supervised video segmentation using (i) motion-based foreground segmentation, (ii) person detection, (iii) static action detection and (iv) object detection. While such segmentation methods might be imperfect, they provide complementary region-level information to local features. We demonstrate how this information can be integrated with BoF representations in a kernel-combination framework. We evaluate our method on the recent and challenging Hollywood-2 action dataset and demonstrate significant improvements.
Data Streams: Models and Algorithms (Advances in Database Systems)

This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.
A young and complex binary star - HD 144432

The southern emission-line star HD 144432 has received considerable attention due to its relative brightness (V ∼ 8.17), its late spectral type (late A-type or perhaps early F) and its relative isolation from a bona-fide active star formation region. We present new imaging and spectroscopic data of this star, which in the past has been classified as both an evolved (post-AGB) object and an isolated Herbig Ae/Be star. We confirm the presence of a faint companion source located 1.4″ north, which appears physically associated with HD 144432. New infrared spectroscopy reveals this companion to be a late-type (early-mid K) star, devoid of any emission lines. Furthermore, we confirm the pre-main sequence nature of this object, report the detection of Li I 6707.8 A absorption toward the HD 144432 system, and its apparent association with Sco OB2-2 located at 145 pc.