Miracle-dz/UniFAR-FTUs huggingface dataset:
Investor Sentiment, Fund Pricing, Performance, and Survival

Using a comprehensive database of passively and actively managed equity mutual funds and exchangetraded products in the United States, this study shows that market-wide investor sentiment at inception predicts fund pricing, performance, and survival. Passive and active funds launched in high-sentiment periods are significantly more expensive than those launched in low-sentiment periods, at inception and thereafter. Also, funds launched in high-sentiment periods underperform on a before-cost basis and are less likely to survive over the short term as well as long term. Together, the results are consistent with fund sponsors exploiting the “windows of opportunity” in high-sentiment periods by launching lower quality investment products.
EFFECT OF MANURE AND HARVESTING AGE ON PHYSICAL AND CHEMICAL PROPERTIES OF PENNISETUM HYBRID SILAGE

This study was conducted to investigate the combined effect of manure type and harvesting age on physical properties and chemical composition of silage produced from Pennisetum hybrid forage. The manure types were from cattle, poultry, swine, goat, while the harvesting times were 4 and 8 weeks after cutback (WAC). Colour results varied significantly (P < 0.05). Dry matter, ether extract, crude fibre, ash, crude protein (CP), neutral detergent fibre, acid detergent fibre and lignin contents of the silage varied significantly (P < 0.05). Higher CP content (91.0 g.kg-1) of the silage was obtained from the interactive effect of poultry or goat manure and 4 WAC harvesting age of Pennisetum hybrid. Higher ash content (330.0 g.kg-1) was recorded for the combined effect of goat manure and 4 WAC on the Pennisetum silage, while the least (70.0 g.kg-1) occurred in grass without manure application sampled 8 WAC. Higher Ca (7.14 g.kg-1) was recorded in silage from swine manure and 4 WAC harvesting age effect. Phosphorus content of the silage was higher (2.57 g.kg-1) with poultry manure and 8 WAC effect, while the least (1.01 g.kg-1 and 1.98 g.kg-1) were from no manure effect at both harvesting ages. Crude protein content of silage made from the Pennisetum hybrid fertilized with either poultry or goat manure and harvested at 4 WAC was the best. Physical properties of the silage were generally of acceptable/desirable grades. With or without the manure application, the minerals of the silage were generally higher than the recommendation of ruminants.
The Nexus between Stock Market Volatility and Economic Growth in Nigeria

The study examines the Nexus between stock market volatility and economic growth in Nigeria. An evaluation of literature on the transmission between stock market volatility and economic growth was conducted resulting into specification of an empirical model. The researchers adapted Generalized Autoregressive Conditional Herteroskedascity (GARCH) and Bivariate GARCH (BGARCH) specifications to account for the relationship between the variables. The study employed quarterly data for the period of 1985 to 2015. The data frequency selected ensured an adequate number of observations. The maximum likelihood estimation technique was adopted to estimate the model. The estimated result reveals that both the stock market return and GDP growth rate have Autoregressive Conditional Herteroskedascity (ARCH) and GARCH effects. This is an indication that there are presence of shocks and evidence of uncertainty in the Nigerian stock market as well as the economic sector. The study concludes that innovation passes through from stock market to the economic sector while on the contrary volatility disconnects and appears un-transmittable from the stock market to the economic sector. Finally, it recommends that government or her representative agent should reposition the economy and make it stable so that it could yield positive innovation that could enhance the expansion of the stock market. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 02-06-2018 Date of acceptance: 18-06-2018 -------------------------------------------------------------------------------------------------------------------------------------
OPTIMIZED ULTRASONIC-ASSISTED EXTRACTION OF TOTAL PHENOLICS AND ANTIOXIDANT ACTIVITY OF DATE (PHOENIX DACTYLIFERA L.) USING RESPONSE SURFACE METHODOLOGY

In the present study, we have optimized the ultrasonic-assisted extraction conditions of total phenolic compounds (TPC) and antioxidant activity of date fruit using response surface methodology (RSM). Three factors including methanol concentration (4080%), sonication amplitude (50-100%) and extraction time (10-30 min) were investigated. The analysis of results with JMP software, using Box-Behnken model, indicated that 65% methanol, ultrasound amplitude of 84.50%, and of extraction time of 17.64 min were the optimal combination that maximized antioxidants extraction. Under the optimized conditions, the experimental values for both TPC and antioxidant activity were 246.46 mg EAG/100g and 26.48 mg EAG/100g, respectively. Predicted models were highly significant (P < 0.01) with high regression coefficients (R ≥ 0.97), while the lack of fit is insignificant. RSM was shown to be an adequate approach for modeling the total phenolic extraction and the antioxidant activity of date palm fruit.
The Feeding Ecology of Grey Gurnard, Eutrigla gurnardus, off the coast of Scotland

Until recently, little research had been conducted into the feeding ecology of grey gurnard (Eutrigla gurnardus), and the species’ wider interaction with the ecosystems it inhabits. This study was carried out to address several questions that have recently arisen about the species. Mainly whether the grey gurnard population at Rockall Bank have been predating on the juvenile haddock to a degree that could cause the stock to decline. This was assessed by conducting a stomach contents analysis on a sample of grey gurnard caught on several trawls. The results of this were inconclusive, with only 3 stomachs containing potential haddock remains out of a total of 121 stomachs. However, these results do not completely disprove the hypothesis, as other factors may have influenced the low fish intake in these gurnard. Furthermore, the populations of grey gurnard from Rockall Bank and the Firth of Forth were compared to determine any differences in feeding ecology between the two. It emerged that the two populations were reasonably similar, with smaller size classes consuming less fish and proportionally more invertebrates, while larger size classes had a diet that was predominantly fish, with the fish prey consisting largely of sand eels. Finally, the influence of fish size on prey selection was investigated, with the result showing a clear correlation between increasing fish size and increasing prey mass, likely owing to the greater amount of fish prey that makes up a larger gurnard’s diet.
Polylingual Tree-Based Topic Models for Translation Domain Adaptation

Topic models, an unsupervised technique for inferring translation domains improve machine translation quality. However, previous work uses only the source language and completely ignores the target language, which can disambiguate domains. We propose new polylingual tree-based topic models to extract domain knowledge that considers both source and target languages and derive three different inference schemes. We evaluate our model on a Chinese to English translation task and obtain up to 1.2 BLEU improvement over strong baselines.
A geometric programming approach to dynamic economic models

Geometric programming (GP) has several attractive features: it is tractable in large-scale problems, requires no initial guess or tuning of solver parameters, guarantees the convergence to a global optimum and can deal with kinks. In this note, I argue that GP is a potentially promising tool in economics. First, I show that a stylized finite-horizon growth model can be mapped into a GP format by using simple transformations. Second, I show that GP methods produce accurate and reliable solutions including the case of occasionally binding constraints which cannot be easily treated with conventional solvers. Examples of MATLAB codes are provided.
Developing an Effective Food Chain Management in a Developing Country: A Case Study on Manalagi Mango Fruit Supply Chain in Indonesia

Carrying out activity efficiently, closing gaps between existing actors’ abilities and those required by the end customer, and a trusted relationship among actors is central to developing an effective fresh fruit supply chain management. A high level of certain activity cost in the chain could indicate the inefficiency built into that activity. The perishable nature of fresh fruit made particular actors in the chain can damage all the efforts taken in another stage to deliver more value to customers. To develop such effective supply chain requires hard work, commitment and a fair degree of trust. Key-words: activity, ability, value, trust
Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models

The Radiation Transfer Model Intercomparison ( RAMI) initiative benchmarks canopy reflectance models under well-controlled experimental conditions. Launched for the first time in 1999, this triennial community exercise encourages the systematic evaluation of canopy reflectance models on a voluntary basis. The first phase of RAMI focused on documenting the spread among radiative transfer (RT) simulations over a small set of primarily 1-D canopies. The second phase expanded the scope to include structurally complex 3-D plant architectures with and without background topography. Here sometimes significant discrepancies were noted which effectively prevented the definition of a reliable "surrogate truth,'' over heterogeneous vegetation canopies, against which other RT models could then be compared. The present paper documents the outcome of the third phase of RAMI, highlighting both the significant progress that has been made in terms of model agreement since RAMI-2 and the capability of/need for RT models to accurately reproduce local estimates of radiative quantities under conditions that are reminiscent of in situ measurements. Our assessment of the self-consistency and the relative and absolute performance of 3-D Monte Carlo models in RAMI-3 supports their usage in the generation of a "surrogate truth'' for all RAMI test cases. This development then leads ( 1) to the presentation of the "RAMI Online Model Checker'' (ROMC), an open-access web-based interface to evaluate RT models automatically, and ( 2) to a reassessment of the role, scope, and opportunities of the RAMI project in the future.
ADVANCES IN THE ANALYSIS OF HUMAN GESTURE RECOGNITION USING KINECT SENSOR: A REVIEW

This paper presents a comprehensive review of human gesture recognition algorithms before and after the release of low cost high resolution depth/RGB Microsoft Kinect sensor. Gesture recognition becomes an active research area in computer vision for the past one or two decades. After the release of Kinect sensor, a number of significant research advances were made particularly in pose estimation considering the depth images. Pose estimation using depth images can address major problems faced by the conventional RGB based approaches. This survey reviews the latest trends in pose estimation using depth images as well as discussing the limitations or problems faced by these approaches. The future research directions are highlighted to improve the current pose estimation algorithms. This paper expected to serve as a reference for the researchers who willing to develop new gesture recognition algorithms based on Microsoft Kinect.
Evaluation of Features in Detection of Dislike Responses to Audio-Visual Stimuli from EEG Signals

There is a strong correlation between the like/dislike responses to audio–visual stimuli and the emotional arousal and valence reactions of a person. In the present work, our attention is focused on the automated detection of dislike responses based on EEG activity when music videos are used as audio–visual stimuli. Specifically, we investigate the discriminative capacity of the Logarithmic Energy (LogE), Linear Frequency Cepstral Coefficients (LFCC), Power Spectral Density (PSD) and Discrete Wavelet Transform (DWT)-based EEG features, computed with and without segmentation of the EEG signal, on the dislike detection task. We carried out a comparative evaluation with eighteen modifications of the above-mentioned EEG features that cover different frequency bands and use different energy decomposition methods and spectral resolutions. For that purpose, we made use of Naive Bayes classifier (NB), Classification and regression trees (CART), k-Nearest Neighbors (kNN) classifier, and support vector machines (SVM) classifier with a radial basis function (RBF) kernel trained with the Sequential Minimal Optimization (SMO) method. The experimental evaluation was performed on the well-known and widely used DEAP dataset. A classification accuracy of up to 98.6% was observed for the best performing combination of pre-processing, EEG features and classifier. These results support that the automated detection of like/dislike reactions based on EEG activity is feasible in a personalized setup. This opens opportunities for the incorporation of such functionality in entertainment, healthcare and security applications.
PAC-Bayes Analysis Beyond the Usual Bounds

We focus on a stochastic learning model where the learner observes a finite set of training examples and the output of the learning process is a data-dependent distribution over a space of hypotheses. The learned data-dependent distribution is then used to make randomized predictions, and the high-level theme addressed here is guaranteeing the quality of predictions on examples that were not seen during training, i.e. generalization. In this setting the unknown quantity of interest is the expected risk of the data-dependent randomized predictor, for which upper bounds can be derived via a PAC-Bayes analysis, leading to PAC-Bayes bounds. Specifically, we present a basic PAC-Bayes inequality for stochastic kernels, from which one may derive extensions of various known PAC-Bayes bounds as well as novel bounds. We clarify the role of the requirement of fixed `data-free' priors and illustrate the use of data-dependent priors. We also present a simple bound that is valid for a loss function with unbounded range. Our analysis clarifies that those two requirements were used to upper-bound an exponential moment term, while the basic PAC-Bayes inequality remains valid with those restrictions removed.
Impact of an enclosure rotation on the activity budgets of two captive giant pandas (Ailuropoda melanoleuca): An observational case study

Captive giant pandas are reported in the literature to perform stereotypic behaviours which are considered to be a behavioural indicator of stress. Although environmental enrichment techniques are commonly used to prevent and/or mitigate performance of stereotypic behaviour in captive giant pandas, evaluation of such techniques is rarely undertaken or reported. This study used behavioural observation methodologies to evaluate the impact of an enclosure rotation as enrichment on the activity budgets of two captive giant pandas, Funi and Wang Wang, housed at the Adelaide Zoo in South Australia. Instantaneous time sampling methods were used to record the giant pandas’ behaviour and location in each enclosure at 180-second intervals over a total of 180 hours (132 baseline hours, 48 post-intervention hours). Following the enclosure rotation, Funi demonstrated a reduction in performance of stereotypic pacing (from 11% of scans at baseline to 4% of scans post-intervention), as well as a notable decrease in frequency of performance of stereotypic somersaults with this aberrant behaviour ceasing completely on the 8th day of data collection post-enclosure rotation. Whilst Wang Wang’s performance of stereotypic pacing remained comparably stable across the study period (about 6 – 7% of scans), the enclosure rotation led to a marked increase in sexual communication behaviours and moderate increases in overall activity. Findings from this case study indicate that enclosure rotations may be an effective behavioural enrichment technique for reducing performance of stereotypic behaviours and increasing behavioural repertoire and activity in zoo-housed giant pandas.
Orchid: A Decentralized Network Routing Market

We present Orchid: a decentralized market for anonymous communication and virtual private networking. Extant privacy solutions are either opaque commercial services with concomitant centralization risks or free peer to peer networks which lack the proper aligned incentives for service quality and economic security at scale. Orchid is a bandwidth market where node providers stake tokens to advertise their services using the Ethereum blockchain. Clients construct single or multi-hop onion routed circuits by selecting nodes randomly weighted on stake and filtered on secondary criteria (price, location, etc.). Staking aligns incentives against operator malfeasance and linear stake weighting in particular neutralizes sybil attacks. Orchid uses a probabilistic payment system which scales to millions of transactions per second, enabling a highly liquid bandwidth market without a trusted central party. Payments at packet scale allow high frequency trustless interactions by reducing the implicit floated balances between transactors to miniscule levels.
OSSEs with a Tornadic Supercell Storm Simulated with a Two-Moment

24 25 The impact of assimilating additional differential reflectivity ZDR data from a polarimetric radar 26 on the analysis of a tornadic supercell storm using an ensemble Kalman filter (EnKF) is studied in 27 an observing system simulation experiment (OSSE) framework assuming a perfect forecast model. 28 A double-moment microphysics scheme is used to allow for proper simulation of polarimetric 29 signatures. Root-mean square errors of analyzed state variables are calculated and the structure 30 and intensity of analyzed fields and derived quantities are examined. Compared to the baseline 31 experiment assimilating radial velocity and reflectivity only, the assimilation of additional ZDR 32 further reduces the errors of all state variables. The analyzed hydrometer fields are improved in 33 both pattern and intensity distributions. Polarimetric signatures including ZDR and KDP columns, 34 and ZDR arc in the supercell are much better reproduced. 35 Sensitivity experiments are performed that exclude the updating of hydrometeor number 36 concentrations by ZDR or of state variables not directly linked to ZDR via observation operators. The 37 results show that if number concentrations are not updated together with the mixing radios, most 38 of the benefit of assimilating ZDR is lost. Among other state variables, the updating of water vapor 39 mixing ratio qv has the largest positive impact while the impact of updating vertical wind w comes 40 in second. The updating of horizontal wind components or temperature has much smaller but still 41 noticeable impact. Reliable flow-dependent cross-covariances among the state variables and 42 observation prior as derived from the forecast ensemble and used in EnKF are clearly very 43
The Effects of Surface Cleaning on Acrylic Emulsion Paintings: A Preliminary Investigation

Conservators frequently report that the removal of surface dirt and grime from acrylic paintings can be problematic. While increasing amounts of research is being published on the analysis of acrylic paints and the historical use of acrylic paints by artists, relatively little has focused on the characterisation of the effects of surface cleaning treatments. One of the current areas of research at Tate is the evaluation of surface cleaning treatments for acrylic paintings, which includes the characterisation of the physical and optical changes to acrylic paint films after cleaning. This forms part of a broad research collaboration on modern paints involving many academic and cultural institutions, such as the National Gallery of Art where researchers are developing chromatographic and spectroscopic methods for the identification of additives in acrylic paints and the characterisation of extractable components. The Getty Conservation Institute (GCI) is continuing to develop techniques and methods for the quantitative identification of modern paints, as well as providing expertise and access to analytical equipment. Tate and GCI have also established a relationship with Exeter Advanced Technologies (X-aT), which has facilitated research into physical properties using thermal analytical techniques.
Reduce violent behavior schizophrenia: A new approach using LT (Laughing therapy) and DRT (Deep relaxation therapy)

Violent behavior is one example of mental disorders that often occur in people’s lives. Based on a preliminary study for 3 months (January, February, March) in 2018 showed that 50-60% of patients treated at Wijaya Kusuma were violent patients. The purpose of this study was to analyze the differences in the effectiveness of DRT and LT in patients with violent behavior. For that, the next investigator is expected to compare the use of other complementary therapies more effective in patients with violent behavior.
Electromagnetically Driven Soft Actuator

Soft active elements will play a leading role in the development of dexterous and compliant robots. We present the fabrication of a soft functional material with ferromagnetic properties capable of producing compressive stress and strain in the presence of magnetic fields. The soft structure consists of a mixture of a super-soft elastomer and 99% pure iron powder. The magnetic and elastic properties of the material were modeled and investigated based on the principles of electromagnetism. These soft actuators reach up to approximately −2700 N/m compressive stress when embedded in a solenoid coil running 7A. Soft actuators were designed to achieve a strain of approximately 17% at 7A. The soft actuators, with their unique capabilities, are promising for employment with soft robots, such as muscle-like structures or flexible actuators.
Iatrogenic Pneumothorax: Incidence and Evaluation of the Therapy

Pneumothorax is defined as the presence of air in the pleural cavity, with secondary lung collapse (1). It is classified as spontaneous pneumothorax, which occurs without any preceding traumatic event and traumatic pneumothorax, which occurs as a result of direct or indirect trauma to the chest. Iatrogenic pneumothorax develops as a result of a diagnostic or therapeutic interventions and is categorized by most investigators as a subdivision of traumatic pneumothorax (1,2). Iatrogenic pneumothorax is a common complication of a variety of procedures such as thoracentesis, pleural biopsy, transbronchial lung biopsy, transthoracic fine needle aspiration, acupuncture, positive pressure ventilation and subclavian venepuncture (3-11). This complication may lead to an increase in cost of medical care and/or to a prolonged hospital stay (3,6). The aim of this present