Miracle-dz/UniFAR-FTUs huggingface dataset:
Back Propagation Neural Network Based Gender Classification Technique Based on Facial Features

The gender recognition system with large sets of training sets for personal identification normally attains good accuracy. The features set is applied to three different applications: Preprocessing, Feature Extraction and Classification. The gender are classified on the basis of distance between eyebrow to eye, eyebrow to nose top, nose top to mouth, eye to mouth, left eye to right eye, width of nose, width of mouth. First to extract these features by using Viola Jones algorithm and then apply Artificial Neural Network. The features set is applied to three different applications: face recognition, facial expressions recognition and gender classification. In this paper described two phases such as feature extraction phase and classification phase. The proposed system produced very promising recognition rates for our applications with same set of features and classifiers.
Smartphone bluetooth based social sensing

The increasing mobile technology raises a new paradigm of people-centric sensing using today's smartphones. Towards this paradigm, we present "CoSoBlue", a novel framework for Bluetooth based social sensing. In CoSoBlue, we propose novel Bluetooth semantic and statistical features, in addition to count and similarity features, and apply these discriminative features to infer context and compute sociability. We evaluate CoSoBlue on two Bluetooth datasets: (1) the longitudinal MIT friend-and-family dataset with 9+ millions records, and (2) a new 2-month dataset with ground-truth labels collected using our own developed Android app. Our primilinary experiments show CoSoBlue's efficacy on Bluetooth based social and context sensing.
How Phonological Structures Can Be Culturally Selected for Learnability

This paper shows how phonological structures can be culturally selected so as to become learnable and adapted to the ecological niche formed by the brains and bodies of speakers. A computational model of the cultural formation of syllable systems illustrates how general learning and physical biases can influence the evolution of the structure of vocalization systems. We use the artificial life methodology of building a society of artificial agents, equipped with motor, perceptual and cognitive systems that are generic and have a realistic complexity. We demonstrate that agents, playing the “imitation game,” build shared syllable systems and show how these syllable systems relate to existing human syllable systems. Detailed experiments study the learnability of the self-organized syllable systems. In particular, we reproduce the critical period effect and the artificial language learning effect without the need for innate biases which specify explicitly in advance the form of possible phonological structures. The ability of children agents to learn syllable systems is explained by the cultural evolutionary history of these syllable systems, which were selected for learnability.
Dissociable Neural Response Signatures for Slow Amplitude and Frequency Modulation in Human Auditory Cortex

Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals.
Induction of apoptosis in small-cell lung cancer cells by an antisense oligodeoxynucleotide targeting the Bcl-2 coding sequence.

BACKGROUND The emergence of resistance to chemotherapy remains a major problem in the treatment of patients with small-cell lung cancer. Elevated expression of Bcl-2, a protein that inhibits programmed cell death or apoptosis, has been associated with radiation and drug resistance and has been observed in the majority of small-cell lung cancer specimens and cell lines. PURPOSE To test the hypothesis that Bcl-2 expression levels are critical for inhibiting apoptosis in small-cell lung cancer cells, we used an antisense strategy to reduce Bcl-2 expression in these cells in an attempt to restore the natural occurrence of apoptosis. METHODS Thirteen antisense oligodeoxynucleotides (ODNs) targeting various regions of the bcl-2 messenger RNA and a control scrambled-sequence ODN were tested to identify the most effective sequence(s) for reducing Bcl-2 protein levels. Northern and western blot analyses were used to examine basal bcl-2 messenger RNA and protein levels, respectively, in four human small-cell lung cancer cell lines (SW2, NCI-H69, NCI-H82, and NCI-N417). SW2 cells were treated with the antisense ODNs in the presence of cationic lipids (to facilitate uptake), and cytotoxic effects were measured by use of a cell viability assay. Flow cytometric analysis of DNA fragmentation and cell morphology was also performed. The cytotoxic effect of the most potent antisense ODN was also tested on the three other cell lines. RESULTS The viability of SW2 cells was effectively reduced by ODNs that targeted the translation initiation and termination sites of the bcl-2 messenger RNA, but ODN 2009 that targeted the coding region was the most cytotoxic. Treatment of SW2 cells with 0.15 microM ODN 2009 for 96 hours reduced their viability by 91% (95% confidence interval [CI] = 88%-94%) and caused a dose-dependent reduction in Bcl-2 levels that became detectable 24 hours after treatment and persisted up to 96 hours; analysis of cellular morphology demonstrated that viability was reduced through apoptosis. Moreover, ODN 2009 at 0.15 microM was cytotoxic to NCI-H69, NCI-H82, and NCI-N417 cells, resulting in decreases in cell viability of 82% (95% CI = 78%-86%), 100%, and 100%, respectively, after 96 hours of treatment. The cytotoxic effects were inversely correlated with the basal Bcl-2 levels in the cell lines (r = -9964). A control scrambled-sequence oligodeoxynucleotide had no statistically significant effect on the cell lines (P values ranging from .38 to .89). CONCLUSION We have identified a novel antisense ODN sequence (ODN 2009) that effectively reduces the viability of small-cell lung cancer cells by reducing Bcl-2 levels and facilitating apoptosis.
A block-based Markov random field model estimation for contextual classification using Optimum-Path Forest

Contextual image classification aims at considering the information about nearby samples in the learning process in order to provide more accurate results. In this paper, we propose a locally-adaptive Optimum-Path Forest classifier together with Markov Random Fields (MRF) that surpasses its naïve version, which was recently presented in the literature. The experimental results over four satellite images demonstrated the proposed approach an outperform previous results, as well as it can perform MRF parameter learning much faster than its former version.
Darwin: an approach for debugging evolving programs

Debugging refers to the laborious process of finding causes of program failures. Often, such failures are introduced when a program undergoes changes and evolves from a stable version to a new, modified version. In this paper, we propose an automated approach for debugging evolving programs. Given two programs (a reference, stable program and a new, modified program) and an input that fails on the modified program, our approach uses concrete as well as symbolic execution to synthesize new inputs that differ marginally from the failing input in their control flow behavior. A comparison of the execution traces of the failing input and the new inputs provides critical clues to the root-cause of the failure. A notable feature of our approach is that it handles hard-to-explain bugs like code missing errors by pointing to the relevant code in the reference program. We have implemented our approach in a tool called DARWIN. We have conducted experiments with several real-life case studies, including real-world web servers and the libPNG library for manipulating PNG images. Our experience from these experiments points to the efficacy of DARWIN in pinpointing bugs. Moreover, while localizing a given observable error, the new inputs synthesized by DARWIN can reveal other undiscovered errors.
Toward Fine-Grained, Unsupervised, Scalable Performance Diagnosis for Production Cloud Computing Systems

Performance diagnosis is labor intensive in production cloud computing systems. Such systems typically face many real-world challenges, which the existing diagnosis techniques for such distributed systems cannot effectively solve. An efficient, unsupervised diagnosis tool for locating fine-grained performance anomalies is still lacking in production cloud computing systems. This paper proposes CloudDiag to bridge this gap. Combining a statistical technique and a fast matrix recovery algorithm, CloudDiag can efficiently pinpoint fine-grained causes of the performance problems, which does not require any domain-specific knowledge to the target system. CloudDiag has been applied in a practical production cloud computing systems to diagnose performance problems. We demonstrate the effectiveness of CloudDiag in three real-world case studies.
SCGA: Controlling Genetic Algorithms with Sarsa(0)

Though deeply analyzing and comparing the mechanism of genetic algorithm and reinforcement learning, a novel algorithm for controlling genetic algorithms using reinforcement learning named SCGA, is proposed and analyzed theoretically. In the existing similar method RL-GA, a reinforcement learning agent uses Q(lambda)-learning to control genetic algorithms. Two problems with such method are that, (1) Q(lambda)-learning cannot fit the stochastic and dynamic characters of genetic algorithms well, and (2) dividing the whole algorithm running time into training and testing schemes reduces its practicability. To solve these drawbacks, SCGA implements the on-policy method Sarsa(0) to control both of the GA operators to choose and the individuals to select without training first. The experimental results show that SCGA learns much faster than RL-GA and the primitive GA on the traveling salesman problem, and is more practicable and scalable in applications
Diffusions causales dans des groupes arbitraires : un protocole simple et efficace

Concepts of group (to structure processes) and causality (to structure sendings and deliveries of messages) are of major importance in the design of distributed systems. Mixing both concepts, the ISIS system defined causal multicast in overlapping groups. This paper presents a simple and efficient protocol that implements such causal multicasts. It compares favourably with the ISIS protocol as it uses only one vector of integers (size of this vector being the total number of groups) to timestamp messages. This low cost in the size of timestamps is obtained by using (sometimes) additional resynchronization messages. It is shown that there is a trade-off between the “as early as possible delivery time” criterium and the “as small as possible timestamps size” criterium for timestamp-based protocols implementing causal order. Key-words: causal order, communication primitive, decentralized system, distributed system, graph of groups, group, multicast, synchronous execution, vector timestamp
SC2: A statistical compression cache scheme

Low utilization of on-chip cache capacity limits performance and wastes energy because of the long latency, limited bandwidth, and energy consumption associated with off-chip memory accesses. Value replication is an important source of low capacity utilization. While prior cache compression techniques manage to code frequent values densely, they trade off a high compression ratio for low decompression latency, thus missing opportunities to utilize capacity more effectively. This paper presents, for the first time, a detailed design-space exploration of caches that utilize statistical compression. We show that more aggressive approaches like Huffman coding, which have been neglected in the past due to the high processing overhead for (de)compression, are suitable techniques for caches and memory. Based on our key observation that value locality varies little over time and across applications, we first demonstrate that the overhead of statistics acquisition for code generation is low because new encodings are needed rarely, making it possible to off-load it to software routines. We then show that the high compression ratio obtained by Huffman-coding makes it possible to utilize the performance benefits of 4X larger last-level caches with about 50% lower power consumption than such larger caches.
Automatic voice-source parameterization of natural speech

We present here our work in automatic parameterization of natural speech by means of a pitch synchronous source-filter decomposition algorithm. The derivative glottal source is modelled using the Liljencrants-Fant (LF) model. The model parameters are obtained simultaneously with the coefficients of an all-pole filter representing the vocal tract response by means of a quadratic programming algorithm. Synthetic data has been created and analyzed in order to show the appropriate function of the estimation method. The parameterization results in high quality synthesized speech for voiced frames. Voice quality extraction is performed on basis to the LF source representation. The inherent modelling of the voice source makes it suitable for voice modification tasks. Work is in progress to add this speech representation to emotional speech synthesis and voice conversion algorithms.
A pilot study of serum selenium, vitamin D, and thyrotropin concentrations in patients with thyroid cancer.

BACKGROUND Low serum selenium concentrations have been associated with a diagnosis of differentiated thyroid cancer in small studies in selenium deficient areas. We conducted a pilot study to explore associations between selenium concentrations and the diagnosis of thyroid cancer in an area of selenium sufficiency in the United States. As low 25-hydroxyvitamin D concentrations have been associated with several malignancies, we also examined 25-hydroxyvitamin D levels. METHODS This study was designed as a pilot study of prediagnostic selenium and 25-hydroxyvitamin D concentrations. We identified 65 euthyroid patients at an academic medical center who were scheduled for thyroidectomy for thyroid cancer, suspicion of thyroid cancer, or nodular disease. Blood samples were obtained two to four weeks prior to thyroidectomy. Samples were analyzed for thyrotropin (TSH), free thyroxine, total triiodothyronine, selenium, and 25 hydroxyvitamin D levels. Concentrations of these analytes were correlated with whether the patient was diagnosed with benign or malignant disease following their thyroidectomy. In patients with thyroid cancer, the concentrations of selenium and 25-hydroxyvitamin D were correlated with various prognostic features. RESULTS Although selenium concentrations were not significantly lower in patients with thyroid cancer, serum selenium concentrations were inversely correlated with disease stage (p = 0.011). There were no associations between vitamin D concentration and a diagnosis of thyroid cancer. Within the thyroid cancer patients, vitamin D concentrations were not associated with disease stage or any other prognostic features. In contrast, TSH concentrations were significantly higher in patients with thyroid cancer, and were positively correlated with the number of involved lymph nodes (p = 0.011) and disease stage (p = 0.022). CONCLUSION These data confirm the association between serum TSH and advanced thyroid cancer. In addition, they also suggest a potential association between selenium concentrations and higher thyroid cancer stage. No such association was seen for 25-hydroxyvitamin D concentrations. Larger prospective studies will be required to confirm this association. If confirmed, future studies would need to determine if the association is causative in nature. If causation exists, it seems likely that selenium concentrations would influence thyroid cancer development via an independent mechanism from that of TSH.
Deposition of Suspended Clay to Open and Sand‐Filled Framework Gravel Beds in a Laboratory Flume

Pulses of fine sediment composed of sand, silt, and clay can be introduced to gravel bed rivers through runoff from burn‐impacted hillslopes, landslides, bank failure, or the introduction of reservoir sediment as a result of sluicing or dam decommissioning. Here we present a study aimed at quantifying exchange between suspensions of clay and gravel beds. The questions that motivate the work are: how do bed roughness and pore space characteristics, shear velocity ( u∗ ), and initial concentration (C0) affect clay deposition on or within gravel beds? Where does deposition within these beds occur, and can deposited clay be resuspended while the gravel is immobile? We examine these questions in a laboratory flume using acrylic, open‐framework gravel, and armored sand‐gravel beds under conditions of varying u∗ and C0. Deposition of clay occurred to all beds (even with Rouse numbers ∼ 0.01). We attribute deposition under full suspension conditions to be an outcome of localized protected zones where clay can settle and available pore space in the bed. For smooth wall cases, protection came from the viscous wall region and the development of bed forms; for the rough beds, protection came from separation zones and low‐velocity pore spaces. Bed porosity was the strongest influencer of nondimensional deposition rate; deposition increased with porosity. Deposition was inversely related to u∗ for the acrylic bed runs; no influence of u∗ was found for the porous bed runs. Increases in discharge resulted in resuspension of clay from acrylic beds; no resuspension was observed in the porous bed runs.
Summer climate implications of tree-ring latewood width: a case study of Tsuga longibracteata in South China

ABSTRACT Summer climate variability in South China at decadal scales is not well understood due to the relatively short meteorological records and the scarcity of paleo-proxies. Herein, we explore the potential of using tree-ring latewood width (LWW) from Tsuga longibracteata to reconstruct summer climatic factors. Latewood usually forms in the mid- to late growing season, at least partly during summer. Tree-ring samples were collected at three sites (HS, QSZ, and SJD) close to the northern boundary of Guangxi province. We built three LWW chronologies and three adjusted LWW chronologies (LWWadj) after the removal of the influence of earlywood on latewood growth. Bootstrapped correlation and response analyses indicate that the LWW chronologies are significantly correlated with summer climatic factors, and the LWWadj chronologies show much higher correlations. The extent to which summer climatic signals can be extracted from LWWadj is site-dependent. At the well-drained sites (QSZ and SJD) with abundant sunshine, LWWadj shows significant positive correlations with July–August Standardised Precipitation-Evapotranspiration Index (SPEI), owing to the positive response to precipitation and the negative response to temperature. In contrast, LWWadj only exhibits positive responses to July temperature on north-oriented slope (HS) with high water-holding capacity. Nearly 37% of the variance in the regional SPEI can be explained by the LWWadj chronology from the forest stand (QSZ) on well-drained southeast-facing slope with less endogenous disturbances. These results indicate that there is a great potential of using LWWadj to reconstruct summer SPEI in South China when suitable sampling sites are selected.
THE EFFECTS OF MELATONIN AND BRIGHT LIGHT THERAPY IN SEASONAL AFFECTIVE DISORDER A PLACEBO CONTROLLED STUDY

Seasonal affective disorder (SAD) is a subsyndromal diagnosis in bipolar disorder or recurrent major depressive disorder, characterized by the recurrence of depressive episodes, which in most cases start in fall or winter and remit in the following spring or summer [American Psychiatric Association, 1994]. Moreover, most patients suffer from atypical symptoms like hyperphagia, hypersomnia, weight gain, fatigue and carbohydrate craving [Rosenthal et al., 1984]. Several studies reported the effectivity of a treatment with bright light [Terman et al., 1989]. As the treatment synchronises the biological clock and the rhythm of the serum melatonin in particular, chronobiological phase shifting is suggested as a possible explanation for the underlying mechanism of bright light therapy [Lewy et al., 1987; Lewy et al., 1988]. Given in the morning, bright light therapy has an acute suppressive effect on the serum melatonin levels and prolongs the subjective day [Lewy et al., 1980]. As melatonin is involved in the synchronisation of the biological clock as Zeitgeber [Rosenthal et al., 1986; Arendt et al., 1987; Rosenthal et al., 1992; Arendt, 1997], administration of melatonin a.n. could have an effect comparable with bright light therapy [Lewy et al., 1998]. This lead to the hypothesis that melatonin a.n. in combination with morning bright light treatment should have an positive additional effect on the treatment of SAD. In this study, the effects of bright light therapy in combination with oral melatonin a.n. or placebo a.n. are evaluated in patients suffering from seasonal affective disorder. In this double blind placebo controlled study, outpatients diagnosed with a seasonal affective disorder according to DSM-IV (major depressive disorder, recurrent with seasonal pattern; 296.3x), without laboratory abnormalities were asked to participate. After giving a written informed consent the patients filled in the SAD version of the Beck Depression Inventory (BDI) [Beck et al., 1961]. Eligible were patients with a score of at least 21 on the BDI at baseline. Excluded were patients with other axis-I pathology, psychotic or manic features, epilepsy, cataract, glaucoma and eye complaints. In the analysis 16 patients were included. Two patients dropped out due to severe side-effects (nausea, anxiety). All patients participating the study were treated with two consecutive weeks (2x5 days) of bright light therapy (BLT). At 8 a.m. the subjects were exposed to 10.000 lux bright light for 30 min. at a distance of 3050 centimetres. The patients were randomised to either melatonin 2.5 mg a.n. (group 1) or placebo (group 2) with identical capsules taken at 10 p.m. each day. Assessments of the severity of the seasonal affective disorder took place before treatment (baseline) and after one, two and six weeks. The Hamilton Rating Scale for Depression, version for seasonal affective disorders