Miracle-dz/UniFAR-FTUs huggingface dataset:
Binarized Neural Networks on the ImageNet Classification Task

We trained Binarized Neural Networks (BNNs) on the high resolution ImageNet ILSVRC-2102 dataset classification task and achieved a good performance. With a moderate size network of 13 layers, we obtained top-5 classification accuracy rate of 84.1 % on validation set through network distillation, much better than previous published results of 73.2% on XNOR network and 69.1% on binarized GoogleNET. We expect networks of better performance can be obtained by following our current strategies. We provide a detailed discussion and preliminary analysis on strategies used in the network training.
DNA Barcode of Seven Indonesian Hornbills Species (Aves: Bucerotidae) Based on Mitochondrial DNA Cytochrome Oxidase Subunit I

DNA barcoding based on mitochondrial DNA COI gene is very useful in identifying of Indonesian hornbill. We sequenced the DNA barcode of seven hornbill species using the mitochondrial DNA COI gene to explore their genetic variation, identity, distance, and phylogenetic. Thirty-one blood samples from seven hornbill species were isolated and analyzed. Slight variation was observed within the nucleotide of the hornbill species. In contrary, fairly significant difference was shown within the genus and family level. COI gene sequences generated from this study, showed unmatched result with BoLD System database. These seven Indonesian hornbill species were then divided into two groups, namely Group I consisting of Aceros cassidix, Rhyticeros plicatus, R. undulatus, Buceros rhinoceros, and B. bicornis, while Group II occupied by Anthracoceros albirostris and A. malayanus; both groups with genetic distance 5.90%. Overall in-group had 9.40% distances to the hornbill used as the out group. COI sequence gene from these seven hornbill species are novel for identifying Indonesian hornbills. We encourage its use as quick species identification, applied to prevent illegal poaching conservation management.
Treatment of peristomal wounds with a topic Neem and Red Hypericum Oil application: Case Studies

Background: Peristomal skin disorders are one of the most frequent complications on the abdominal stoma. Currently therapeutic approaches do not take into account the specific characteristics of this type of wound. Objectives: To assess in a first series of patients not responding to treatment with traditional dressings, the effectiveness of a topic wound dressing with Neem Oil and Red Hypericum Oil, applied so as to guarantee the adhesiveness of the pouching system. This product, currently indicated to treat wounds of all aetiologies, acts as antimicrobial, bacteriostatic and mechanical barrier and promotes natural tissue repair. Methods: The two patients we enrolled presented peristomal wounds not responding to treatment with traditional dressings. To comply with the need of applying adhesive pouching we had to devise a suitable wound dressing. The patients were treated twice weekly, by applying the product on an hydrofiber dressing support, protected by a transparent film. No local antiseptics were used. Results: Complete healing of the lesions, in the first case after 14 days, in the second after 28 days, with immediate pain decrease. Both patients showed a positive attitude towards the treatment. The dressing design allowed the appliance to remain in place for three days with no complications. Conclusions: The use of the Neem Oil and Red Hypericum Oil dressing can be a valid therapeutic solution in the treatment of difficult to heal peristomal wounds, and therefore deserves to be confirmed through studies involving a higher number of patients.
Global and Local Bursts Detection in Streaming Data

Identifying and analyzing peaks in given data stream is valuable for many real time applications. The abnormal activities in network, sudden increase in price/volume and sharp rise in demands are discovered by detecting peaks in real time stream. To devise algorithms to automatically detect peaks in any given streaming data, formalized ways of peak notation is needed. An unexpectedly large number of frequencies occurring within some certain measurement are called a burst. Thus the nature of peak detection is similar to burst detection in this study because threshold based bursts detection is used. The burst detection is the maximum number of frequency of words per interval of time. The local burst in streaming data means data point which has large and locally high frequency value within time period which called windows. It is also isolated because it has not too many points in the window which have similar values. Not all local bursts are true burst; a local burst is a true burst if it is a reasonably large value even in the global context. Bursts come up in many natural and social processes. It is a challenging task to monitor the occurrence of bursts whose lasting duration is unknown in a fast data stream environment. We present a greedy dynamic detection algorithm which monitors sampling time window size by proportionally the rate of data arrival. It evolves the adaptive methods to adapt sampling time window size and burst defines thresholds to define local burst.
Perception of burden by caregivers of patients with schizophrenia in relation to symptom profile

Background: Schizophrenia begins early in life causing significant long-lasting impairments. The caregivers face physical, psychological, and economic difficulties in taking care of them. The current study was undertaken to study the influence of symptomatology, duration of illness, and treatment compliance of patients with schizophrenia on caregivers' burden. Methods: This study was hospital based, clinical, instrument rated, and cross sectional. Eighty-five patients and their caregivers who satisfied the selection criteria were interviewed. Information regarding sociodemographic details, patients' illness, present psychopathology, and relatives' burden were collected. Scale for Assessment of Negative Symptoms and Scale for Assessment of Positive Symptoms for (patients) and Burden Assessment Schedule for caregivers was used in the study. Descriptive and inferential statistical analysis was used. Results: The present study found that positive symptoms caused greater burden when compared to negative symptoms. Burden increased with increasing severity of negative symptoms. Although no significant influence of duration of illness and compliance to treatment was seen on caregivers' perception of burden, differential effect of the burden was observed for the above variables. Conclusions: Adequate treatment of symptoms benefits both patients and their caregivers. There is need for proper education of the patient and the caregivers about the need for continued treatment. The current study corroborates the importance of adequate treatment of positive symptoms as well as negative symptoms and the need to address caregiving by the family members for the well-being of both.
A Review on Economic Load Dispatch Using Evolutionary Technique

Economic load dispatch is an important optimization problem in power system. Economic dispatch is the short-term determination of the optimal output of a number of electricity generation facilities, to meet the system load, at the lowest possible cost, subject to transmission and operational constraints. The Economic Dispatch Problem is solved by specialized computer software which should honor the operational and system constraints of the available resources and corresponding transmission capabilities This paper presents a review on evolutionary methods for solving economic load dispatch problem which mainly include Genetic Algorithm based approach, Particle Swarm Optimization (PSO), Differential Evolution (DE) which will encourage the researches for providing better solution for economic load dispatch problem.
Consistency Check Between UML Sequence Diagram and Statechart

UML can be used to accomplish the system modeling from different views.There are information redundancy in different views, so that the views may be inconsistent.This paper proposes an approach to analyze sequence diagram which has many different logical semantics.To deal with the hierarchy structure of statechart, finite state automata is used in this paper, and an automata decomposition algorithm is proposed to get an automata tree.A new model consistency criterion of sequence diagram and statechart, as well as a new structure of Promela is proposed.Model consistency is checked between sequence diagram and statechart with the model checker SPIN.
A Temporal and Spatial Correlation Based Missing Values Imputation Algorithm in Wireless Sensor Networks

In wireless sensor networks,the missing of the sensing data is inevitable due to the inherent characteristic of wireless sensor networks,and it causes many difficulties in various applications.To solve the problem,the best way is to estimate the missing values as accurately as possible.In this paper,a temporal correlation based missing values imputation algorithm is proposed firstly.It adopts linear interpolation model to estimate the missing values and a good estimation effect can be achieved for the sensing data changing smoothly in a short time.Next,a spatial correlation based missing values imputation algorithm is proposed.It adopts multiple regression model and estimates the missing values with the data of multiple neighbor nodes jointly rather than independently,so that it can achieve a good estimation effect even for the sensing data that changing non-smoothly.Besides,it can not only give the estimated values of the missing data,but also give the confidence interval of each missing data for the given confidence level.Based on these two algorithms,an adaptive temporal and spatial correlation based missing values imputation algorithm is proposed at the end of this paper.It performs well both for the sensing data changing smoothly and non-smoothly.Experimental results on a real-world dataset show that the proposed algorithms can estimate the missing values accurately.
Comparison of lymphocyte immune phenotypes in bronchoalveolar lavage of non-smoking patients with sarcoidosis and other interstitial lung diseases.

Background Bronchoalveolar lavage (BAL) as complementary method is still used as ancillary tool in diagnosis of interstitial lung diseases. Tobacco smoking has been described to affect the BAL lavage cellular profile. To our knowledge, only few reports have so far investigated CD3+CD4+ and CD3+CD8+ lymphocyte subsets in non-smoking sarcoidosis patients additionally stratified according to CXR stage, and compared them to other non-smoking patients with interstitial lung diseases (ILDs). Methods We compared lymphocytes immune phenotypes, subsets, with CD3+, CD3+CD4+ and CD3+CD8+ cell markers, in the non-smoking subjects (n=297) including the patients with pulmonary sarcoidosis (S), idiopathic pulmonary fibrosis (IPF) (n=22), hypersensitivity pneumonitis (HP) (n=15), other interstitial idiopathic pneumonias (OIIPs) (n=39). According to prognosis, the patients with S were divided into four groups: 18 patients with Löfgren's syndrome (LS) in chest X-ray (CXR) ≤1 stage, 64 patients without LS in CXR ≤1 stage, 113 patients in CXR 2 stage and 26 patients with advanced CXR ≥3 stage. Results After the use of false discovery rate (FDR) correction, relative numbers (%) of CD3+, CD3+CD4+, CD3+CD8+ and CD3+CD4/CD3+CD8 ratio showed the most significant differences between the non-smokers with S (both with/without LS) and the non-smokers with other ILDs (IPF, OIIPs, HP). These lymphocytes subsets were further altered in the non-smokers with CXR stage 2 compared to the non-smokers with other ILDs (IPF, OIIPs, HP). We did not observe any differences in these lymphocyte subsets and CD3+CD4+/CD3+CD8+ ratio between the non-smokers with advanced sarcoidosis stage (CXR ≥3) and the non-smokers with IPF. Conclusions Our data on the non-smokers confirmed the presence of the typical BAL cellular profile in sarcoidosis. The BAL cellular profile was helpful namely for differentiation of less advanced sarcoidosis. Its definite diagnostic utility should be the subject of further clinical studies with large numbers of the well characterized patients taking into consideration other clinical factors influencing BAL cellular profile, such as smoking or treatment.
Use of Wearable Technology and Social Media to Improve Physical Activity and Dietary Behaviors among College Students: A 12-Week Randomized Pilot Study

College students demonstrate poor physical activity (PA) and dietary behaviors. We evaluated the feasibility of a combined smartwatch and theoretically based, social media-delivered health education intervention versus a comparison on improving college students’ health behaviors/outcomes. Thirty-eight students (28 female; Xage = 21.5 ± 3.4 years) participated in this two-arm, randomized 12-week pilot trial (2017–2018). Participants were randomized into: (a) experimental: Polar M400 use and twice-weekly social cognitive theory- and self-determination theory-based Facebook-delivered health education intervention; or (b) comparison: enrollment only in separate, but content-identical, Facebook intervention. Primary outcomes pertained to intervention feasibility. Secondary outcomes included accelerometer-estimated PA, physiological/psychosocial outcomes, and dietary behaviors. Intervention adherence was high (~86%), with a retention of 92.1%. Participants implemented health education tips 1–3 times per week. We observed experimental and comparison groups to have 4.2- and 1.6-min/day increases in moderate-to-vigorous PA (MVPA), respectively, at six weeks—partially maintained at 12 weeks. In both groups, similarly decreased body weight (experimental = −0.6 kg; comparison = −0.5 kg) and increased self-efficacy, social support, and intrinsic motivation were observed pre- and post-intervention. Finally, we observed small decreases in daily caloric consumption over time (experimental = −41.0 calories; comparison = −143.3). Both interventions were feasible/of interest to college students and demonstrated initial effectiveness at improving health behaviors/outcomes. However, smartwatch provision may not result in an additional benefit.
Jitter Correction of the Face Motion Capture Data for 3D Animation

Along with the advance of digital technology, various methods are adopted for capturing the 3D animating data. Especially, in 3D animation production market, the motion capture system is widely used to make films, games, and animation contents. The technique quickly tracks the movements of the actor and translate the data to use as animating character’s motion. Thus the animation characters are able to mimic the natural motion and gesture, even face expression. However, the conventional motion capture system needs tricky conditions, such as space, light, number of camera etc. Furthermore the data acquired from the motion capture system is frequently corrupted by noise, drift and surrounding environment. In this paper, we introduce the post production techniques to stabilizing the jitters of motion capture data from the low cost handy system based on Kinect.
Evaluation of macula, optic nerve and choroid in children with joint hypermobility

Aim: To evaluate the macula, optic nerve and choroid layer by using Spectral Domain (SD)-OCT in children with joint hypermobility (JH) Material and Methods: In this cross-sectional case control study, 25 eyes of 25 children with JH diagnosed by rheumatological examination and 37 eyes of 37 healthy children were evaluated. Images were taken with SD -OCT. Two groups were compared in terms of mean central macular thickness, macular volume, ganglion cell complex (GCC) thickness, retina nerve fiber layer (RNFL) thickness and choroidal thickness (CT). CT was measured at the fovea; other CT measurements were taken 1,000 Âµm away from the fovea at the nasal and temporal regions and 1000 Âµm away from the optic disc at the nasal and temporal regions. Results: Mean subfoveal CT was 293. 85Â±40.74 Âµm in JH group and 301. 66Â±49.47 Âµm in the control group (p=0.548). There was no significant difference regarding to the mean macular and peripapillary CT values of all regions (P >0 .05 for all points). Moreover, the mean thicknesses of the RNFL, macula, and GCC did not differ between the two groups. Conclusion: This study showed that CT of children with JH is similar to those of healthy controls. In addition, there was no difference in macular thickness, RNFL and GCC between the two groups. These findings suggest that posterior segment structures are not affected in individuals with JH.
Read all about it: Do auditors respond to press visibility?

I examine whether auditors respond to business press coverage. Using the number of articles covering a client firm (a proxy for visibility) I find that auditors charge higher audit fees for clients with higher visibility incremental to other determinants of fees. The audit fee evidence is corroborated using other proxies for auditor decisions: audit report modifications, the level of accruals, and auditor turnover. The evidence suggests that auditors respond to risks driven by press coverage. I conclude that the press not only participates in the external monitoring of financial reporting, but that through its influence on official external monitors the press actually also affects financial reporting.
Anti-occlusion object tracking algorithm based on fused texture feature Mean-shift

In traditional Mean-shift algorithm only the color features of object was used.When the scene contained a object with color similar to the tracked object color,an error tracking would happen.When the object was occluded,the object could not be tracked effectively.An anti-occlusion object tracking method with fused texture features of the object was proposed.Meantime,the template was updated,and the Kalman filter was used for object estimation and prediction when the object was occluded.An object-occlusion factor was also proposed as object occlusion criterion.When the object was occluded seriously,the object location would be predicted with extrapolation of object state.Experimental result showed that this method exhibited a stronger anti-interference and could be used to track correctly the object in complete occlusion.
WHEN BRAIN STIMULATION BACKFIRES

OF DISSERTATION WHEN BRAIN STIMULATION BACKFIRES tDCS brain stimulation does not always work in the intended direction. It has been found to sometimes worsen behavior rather than improve it. A preliminary study shows that people high on sensation-seeking and lack of premeditation were prone to reverse effects of tDCS on performance on a Stop Signal Task. Both of these constructs are related to dopamine levels. Study 2 seeks to intentionally cause a reverse effect of tDCS by increasing participants’ dopamine levels via caffeine. There was not a significant interaction between tDCS and caffeine on errors on the Stop Signal Task in this study. However, other factors interacted with tDCS and caffeine including lack of premeditation. This two study package suggests the effects of tDCS are variable across individuals, with personality and neurochemistry both affecting behavioral outcomes of tDCS.
Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection

This chapter presents an efficient approach to personalized pronunciation assessment of Taiwaneseaccented English. The main goal of this study is to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed assessment help quickly discover personalized mispronunciations of a student, thus English teachers can spend more time on teaching or rectifying students’ pronunciations. In this approach, an unsupervised model adaptation method is performed on the universal acoustic models to recognize the speech of a specific speaker with mispronunciations and Taiwanese accent. A dynamic sentence selection algorithm, considering the mutual information of the related mispronunciations, is proposed to choose a sentence containing the most undetected mispronunciations in order to quickly extract personalized mispronunciations. The experimental results show that the proposed unsupervised adaptation approach obtains an accuracy improvement of about 2.1% on the recognition of Taiwanese-accented English speech. DOI: 10.4018/978-1-4666-1830-5.ch002
Comparative Study of Prophet, MaxProp, Source Spray and Wait and Binary Spray and Wait Protocols in Delay Tolerant Networks

Delay-tolerant Networking (DTN) makes successful communication in sparse mobile ad-hoc networks and other challenged environments with verities of protocols. In this paper we have analyzed performance of various protocols that use replication and flooding mechanism to transfer message between nodes. Through the evolution of all routing protocol in with various numbers of nodes using simulation tool comparative study can be done. This paper focus on the performance of Prophet, MaxProp, Source Spray and Wait Routing Protocol and Binary Spray and Wait Routing protocol in random way point mobility model.
Adaptive Clinical Trial Designs with Surrogates: When Should We Bother?

The success of a new drug is assessed within a clinical trial using a primary endpoint, which is typically the true outcome of interest—for example, overall survival. However, regulators sometimes approve drugs using a surrogate outcome—an intermediate indicator that is faster or easier to measure than the true outcome of interest—for example, progression-free survival—as the primary endpoint when there is demonstrable medical need. Although using a surrogate outcome (instead of the true outcome) as the primary endpoint can substantially speed up clinical trials and lower costs, it can also result in poor drug-approval decisions because the surrogate is not a perfect predictor of the true outcome. In this paper, we propose combining data from both surrogate and true outcomes to improve decision making within a late-phase clinical trial. In contrast to broadly used clinical trial designs that rely on a single primary endpoint, we propose a Bayesian adaptive clinical trial design that simultaneously leverages both observed outcomes to inform trial decisions. We perform comparative statics on the relative benefit of our approach, illustrating the types of diseases and surrogates for which our proposed design is particularly advantageous. Finally, we illustrate our proposed design on metastatic breast cancer. We use a large-scale clinical trial database to construct a Bayesian prior and simulate our design on a subset of clinical trials. We estimate that our design would yield a 16% decrease in trial costs relative to existing clinical trial designs, while maintaining the same Type I/II error rates. This paper was accepted by J. George Shanthikumar for the Special Issue on Data-Driven Prescriptive Analytics.