Miracle-dz/UniFAR-FTUs huggingface dataset:
A Solution in Search of a Problem: A Method for the Development of Blockchain Use Cases

Blockchain technology is a very recent and fast evolving phenomenon with the potential to disrupt various industries. Organizations are thus increasingly looking at blockchain technology and are forming multifunctional teams to evaluate the technology and its impact on their businesses. Researchers and practitioners, however, still lack a technology-driven, systematic approach to understand the potential of blockchain and to develop convincing use cases. We addressed this research gap by applying an action design research approach and situational method engineering to propose a method for the development of blockchain use cases. Following this approach, we iteratively evaluated and further developed the proposed method through application and testing in four distinct industries. We thus derive constructive knowledge at the cutting edge of digital transformation, innovation management, and utilization of emerging technologies. In addition, our research supports practitioners in systematically developing blockchain use cases.
Environmental risk assessment of replication competent viral vectors in gene therapy trials

Het RIVM heeft een methode uitgewerkt waarmee de risico's voor mens en milieu van replicatiecompetente virussen als kankertherapie kunnen worden beoordeeld. Zo'n methode bestond nog niet. De verwachting is dat de risicobeoordeling, en daarmee de vergunningverlening, van klinische studies die gebruikmaken van genetisch gemodificeerde replicerende virussen hierdoor kan worden bespoedigd. Nederlandse onderzoekers zijn van plan om klinische studies te starten waarbij gebruik zal worden gemaakt van virussen die in staat zijn zich te vermenigvuldigen (replicatiecompetent). Dit zijn genetisch gemodificeerde virussen die zich in kankercellen kunnen vermenigvuldigen en ze op die manier kunnen vernietigen. Mogelijke schadelijke effecten van gentherapieen met een virus zijn gekoppeld aan de mate waarin mens en milieu aan het virus worden blootgesteld. In Nederland zijn tot nu toe uitsluitend virussen die zich niet meer kunnen vermenigvuldigen als therapie toegepast. Deze 'kreupele' virussen infecteren een beperkt aantal cellen en kunnen bijvoorbeeld een genetisch defect in een patient met een stofwisselingsziekte opheffen. Uit de risicobeoordeling blijkt dat in de meeste gevallen de risico's hiervan voor mens en milieu verwaarloosbaar klein zijn. Een belangrijk uitgangspunt in de risicobeoordeling van replicatiecompetente virussen is dat er een zekere kans is dat de toegepaste virussen zich vanuit de patient in het milieu verspreiden. Replicatiecompetente virussen hebben immers eigenschappen waardoor ze zich binnen een patient kunnen vermenigvuldigen. In de aanbevelingen voor de milieurisicoanalyse wordt rekening gehouden met deze eigenschappen, de eventuele effecten van de genetische modificaties op het virus, de huidige klinische toepassingen en toekomstige ontwikkelingen. Het rapport biedt handvatten voor zowel risicobeoordelaars en beleidsmakers als voor aanvragers van een introductie in het milieu vergunning om gentherapiestudies uit te mogen voeren.
Impact of CPO export duties on Malaysian palm oil industry

In January 2013, Malaysia reduced the export duty s tructure to be in line with the Indonesia’s duty structure. Both countries export crude and processe d palm oil. Since Malaysia and Indonesia are close competitors and they compete in the same market, a change in export duty rate in one country will affe ct the other. Indonesia, as the world’s biggest palm oil p roducer, has drastically widened the values between the crude palm oil and refined palm oil export taxes si nce October 2011, to encourage more downstream investments and production of refined palm oil prod ucts. Under the revised export duty structure, crud e palm oil and crude palm kernel oil are cheaper for downstream activities in Indonesia. The new structu re is expected to reduce Malaysia’s competitiveness in th e world market as its export duty is relatively hig her. A high export duty results in high price of crude pal m oil which is the raw material for processed palm oil. The research questions are: (i) What are the likely future trends of crude palm oil exports under the new crude palm oil export duties? Will it increase, red uce or stabilize? (ii) What are the likely future t rends of processed palm oil exports? Will it increase expone ntially, stabilize or reduce? To answer these quest ions, a system dynamics model was developed for the Malaysian palm oil. Application of the system dynamics model provides a framework to understand the feedback structure and how changes in variables impact th e behavior of the palm oil industry. This research su ggests that with low crude palm oil export duties c rude palm oil domestic price, profitability of plantatio n owners, immature crop, mature crop, total planted area, production and exports of crude palm oil increase, however exports of processed palm oil decrease.
A simulated observation database to assess the impact of the IASI-NG hyperspectral infrared sounder

Abstract. The highly accurate measurements of the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) are used in numerical weather prediction (NWP), atmospheric chemistry and climate monitoring. As the second generation of the European Polar System (EPS-SG) is being developed, a new generation of IASI instruments has been designed to fly on board the MetOp-SG constellation: IASI New Generation (IASI-NG). In order to prepare the arrival of this new instrument, and to evaluate its impact on NWP and atmospheric chemistry applications, a set of IASI and IASI-NG simulated data was built and made available to the public to set a common framework for future impact studies. This paper describes the information available in this database and the procedure followed to run the IASI and IASI-NG simulations. These simulated data were evaluated by comparing IASI-NG to IASI observations. The result is also presented here. Additionally, preliminary impact studies of the benefit of IASI-NG compared to IASI on the retrieval of temperature and humidity in a NWP framework are also shown in the present work. With a channel dataset located in the same wave numbers for both instruments, we showed an improvement of the temperature retrievals throughout the atmosphere, with a maximum in the troposphere with IASI-NG and a lower benefit for the tropospheric humidity.
Metronomic capecitabine versus doxorubicin in advanced hepatocellular carcinoma

Liver cancer is the fifth most common cancer worldwide and the third most common cause of cancer mortality with more than 500,000 deaths annually. Hepatocellular carcinoma (HCC), the most common primary liver cancer, occurs in the setting of chronic liver disease and cirrhosis and is usually diagnosed late with a median survival following diagnosis of approximately 6 to 20 months [1]. HCC is clearly associated with hepatitis B and hepatitis C viral infections and chronic liver disease [2]. In Egypt, according to the 2002–2003 cancer registry, liver malignancies account for 7.5% of all cancer cases [3]. In a single center evaluation, HCC was reported to account for about 4.7% of chronic liver disease patients. Hospital-based studies have reported an overall increase in the relative frequency of all liver related cancers (95% as HCC), from approximately 4% in 1993 to 7.3% in 2003 [4]. Prognosis of HCC and treatment options are determined by anatomical extent of tumor (stage), biological aggressiveness (grade), cirrhosis severity (indicated by the Child-Pugh classification) and functional status. Treatment options for HCC are divided into surgical therapies (resection, cryoablation, and liver transplantation) and nonsurgical therapies, which may be liver-directed (percutaneous ethanol injection, radiofrequency ablation, transarterial chemoembolization, radiation and radioembolization) or systemic treatment (chemotherapy, molecularly targeted therapy and hormone therapy) [5]. Original Article Korean Journal of Clinical Oncology 2016;12:32-40 http://dx.doi. org/10.14216/kjco.16006 pISSN 1738-8082 ∙ eISSN 2288-4084
Effectiveness of replacing catalytic converters in LPG-fueled vehicles in Hong Kong

Abstract. Many taxis and public buses are powered by liquefied petroleum gas (LPG) in Hong Kong. With more vehicles using LPG, they have become the major contributor to ambient volatile organic compounds (VOCs) in Hong Kong. An intervention program which aimed to reduce the emissions of VOCs and nitrogen oxides (NOx) from LPG-fueled vehicles was implemented by the Hong Kong government in September 2013. Long-term real-time measurements indicated that the program was remarkably effective in reducing LPG-related VOCs, NOx and nitric oxide (NO) in the atmosphere. Receptor modeling results further revealed that propane, propene, i-butane, n-butane and NO in LPG-fueled vehicle exhaust emissions decreased by 40.8 ± 0.1, 45.7 ± 0.2, 35.7 ± 0.1, 47.8 ± 0.1 and 88.6 ± 0.7 %, respectively, during the implementation of the program. In contrast, despite the reduction of VOCs and NOx, O3 following the program increased by 0.40 ± 0.03 ppbv (∼ 5.6 %). The LPG-fueled vehicle exhaust was generally destructive to OH and HO2. However, the destruction effect weakened for OH and it even turned to positive contribution to HO2 during the program. These changes led to the increases of OH, HO2 and HO2 ∕ OH ratio, which might explain the positive O3 increment. Analysis of O3–VOCs–NOx sensitivity in ambient air indicated VOC-limited regimes in the O3 formation before and during the program. Moreover, a maximum reduction percentage of NOx (i.e., 69 %) and the lowest reduction ratio of VOCs ∕ NOx (i.e., 1.1) in LPG-fueled vehicle exhaust were determined to give a zero O3 increment. The findings are of great help to future formulation and implementation of control strategies on vehicle emissions in Hong Kong, and could be extended to other regions in China and around the world.
Usability Study of Distributed Deep Learning Frameworks For Convolutional Neural Networks

With the popularity of deep learning, the increasing complexity of deep learning models, and the availability of very large datasets, model training has become a time-consuming process. One way to make this process efficient is to distribute training across multiple GPUs and nodes, and many deep learning frameworks now support distributed training. In this paper, we survey the various distributed versions of popular deep learning frameworks. We analyze their performance from the practitioner’s point of view and compare them on the basis of various indicators including time, memory, and accuracy. We show that there are measurable differences between various frameworks. We also provide a qualitative comparison that measures community popularity, functionality, compatibility, and ease-of-use. We believe this multi-faceted comparison will allow practitioners to make an informed choice on which framework to use when conducting distributed training of deep learning models. We also open source the benchmark pipeline so that newer frameworks (or newer versions of existing frameworks) may be compared as and when they become available.
Temporal and geographical variation in monarch densities: Citizen scientists document monarch population patterns

timing of autumn monarch migrations (Walton and Brower 1996; Calvert and Wagner 1999); the Journey North program monitors the timing of the spring migration (Donnelly 1999; Howard and Davis, this volume); and researchers in Mexico monitor the size of the overwintering monarch colonies (GarcíaSerrano and Alvarez 1999; García-Serrano et al., this volume). Missing in this array of programs is a study of monarch egg and larval populations. By monitoring immature stages, we can measure the temporal and spatial variation in monarch reproduction and learn more about how monarchs use the available habitat. We can also compare population statistics on immature stages to those estimated for summer, fall, and winter adult populations to identify how population size at one stage affects that at later stages.
Introduction of Innovative Equipment in Mining: Impact on Occupational Health and Safety

Occupational health and safety in mining has clearly improved in developed countries over the past twenty years, but accidents and illness still occur with unacceptable frequency. The arrival of new mining equipment, bigger, more powerful and complex and requiring a higher skill level appears also to increase certain specific risks of accident and work-related illness. The objective of this paper is to examine the impact of new equipment on occupational health and safety in underground mining. The injury rate associated with eight equipment introduction projects was examined. The results show clearly that the introduction of new equipment with technological innovations does not automatically reduce the injury rate. The new equipment may even generate a higher injury rate than the equipment it replaced. Ergonomic deficiencies were noted in some of the new equipment. We suggest that future research focus on identifying the mechanisms and conditions that determine injury rate following the acquisition of innovative as means of improving occupational health and safety in mining. Successful implementation of new mining equipment appears to depend on the specific conditions of use.
Formulation, Physicochemical, Nutritional and Sensorial Evaluation of Corn Tortillas Supplemented with Chía Seed

Rendon-Villalobos R. , Ortiz-Sanchez A. , Solorza-Feria J., Trujillo-Hernandez C.A . (2012): Formulation, physicochemical, nutritional and sensorial evaluation of corn tortillas supplemented with chia seed (Salvia hispanica L.). Czech J. Food Sci., 30: 118–125. Composite flours containing 5%, 10%, 15%, and 20% of chia seed flour and corn were used for tortilla formulations. The effects of chia powders supplementation on the physicochemical and sensorial characteristics as well as starch digestibility of the tortillas were evaluated. Nutritionally, all chia tortillas had significantly higher levels ( P 0 .05) differences in the attributes among tortillas. Owing to the increase in the total dietary fibre, lower digestion, and predicted glycemic index values, chia seed-added tortilla can be considered as a nutraceutical food. Therefore, the newly developed tortilla supplemented with chia seed flour could represent a valuable staple in improving the nutritional value of the original food product.
Resistant hypertension: Definition, evaluation, and new therapeutic approaches to treatment

Resistant hypertension is defined as blood pressure above the patient’s goal despite the use of 3 or more antihypertensive agents from different classes at optimal doses, one of which should ideally be a diuretic. Although the exact prevalence of resistant hypertension is currently unknown, indirect evidence from population studies and clinical trials suggests that it is a relatively common clinical problem. The prevalence of resistant hypertension is projected to increase, owing to the aging population and increasing trends in obesity, sleep apnea, and chronic kidney disease. Evaluation of patients with resistive hypertension should first confirm that they have true resistant hypertension by ruling out or correcting factors associated with pseudoresistance such as white coat hypertension, suboptimal blood pressure measurement technique, poor adherence to prescribed medication, suboptimal dosing of antihypertensive agents or inappropriate combinations, the white coat effect, and clinical inertia. Management includes lifestyle and dietary modification, elimination of medications contributing to resistance, and evaluation of potential secondary causes of hypertension. Education and reinforcement of life-style issues that affect BP, such as sodium restriction, reduction of alcohol intake, and weight loss if obese, are critical in treating resistant hypertension. Pharmacological treatment should be tailored to the patient’s profile and focus on the causative pathway of resistance. Exclusion of preparations that contribute to true BP treatment resistance, such as nonsteroidal anti-inflammatory agents, cold preparations, and certain herbs, is also important. Lastly, BP control can only be achieved if an antihypertensive treatment regimen is used that focuses on the genesis of the hypertension. An example is volume overload, a common but unappreciated cause of treatment resistance. Use of the appropriate dose and type of diuretic provides a solution to overcome treatment resistance in this instance. Patients with uncontrolled hypertension despite receiving an optimal therapy are candidates for newer interventional therapies such as carotid baroreceptor stimulation and renal denervation. Correspondence to: Maria Leonarda De Rosa, Department of Translational Medical Sciences, University of Naples Federico II, Italy, Email: mlderosa@ unina.it
Determinants of Customer Satisfaction and Dissatisfaction toward Hotels among Various Demographic Groups of Customers ( Full Paper Submission )

Electronic word-of-mouth effects generated by online reviews play an important role in influencing hotels’ demand. Using a text mining approach, Latent Semantic Analysis, we analyze online customer reviews toward hotels. We find the determinants of customer satisfaction and dissatisfaction toward hotels are different and not equally important among the six demographic groups of customers, including families with older children, families with younger children, mature couples, groups of friends, solo travelers, and young couples. Our study provides implications for hoteliers to improve service performance by enhancing customer satisfaction and alleviating customer dissatisfaction, and using market segment strategies toward various customer groups.
Optimal model for path loss predictions using feed-forward neural networks

Abstract In this paper, an optimal model is developed for path loss predictions using the Feed-Forward Neural Network (FFNN) algorithm. Drive test measurements were carried out in Canaanland Ota, Nigeria and Ilorin, Nigeria to obtain path loss data at varying distances from 11 different 1,800 MHz base station transmitters. Single-layered FFNNs were trained with normalized terrain profile data (longitude, latitude, elevation, altitude, clutter height) and normalized distances to produce the corresponding path loss values based on the Levenberg–Marquardt algorithm. The number of neurons in the hidden layer was varied (1–50) to determine the Artificial Neural Network (ANN) model with the best prediction accuracy. The performance of the ANN models was evaluated based on different metrics: Mean Absolute error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), standard deviation, and regression coefficient (R). Results of the machine learning processes show that the FNN architecture adopting a tangent activation function and 48 hidden neurons produced the least prediction error, with MAE, MSE, RMSE, standard deviation, and R values of 4.21 dB, 30.99 dB, 5.56 dB, 5.56 dB, and 0.89, respectively. Regarding generalization ability, the predictions of the optimal ANN model yielded MAE, MSE, RMSE, standard deviation, and R values of 4.74 dB, 39.38 dB, 6.27 dB, 6.27 dB, and 0.86, respectively, when tested with new data not previously included in the training process. Compared to the Hata, COST 231, ECC-33, and Egli models, the developed ANN model performed better in terms of prediction accuracy and generalization ability.
Attenuation and modification of the ballast water microbial community during voyages into the Canadian Arctic

Ballast water is a major vector of non‐indigenous species introductions world‐wide. Our understanding of population dynamics of organisms entrained in ballast is largely limited to studies of zooplankton and phytoplankton. Bacteria are more numerous and diverse than zooplankton or phytoplankton, yet remain comparatively understudied. We apply a metagenomics approach to characterize changes in the microbial ballast water community over the course of three voyages on one ship, and assess the effects of ballast water exchange (BWE), spring/summer sampling month and time since voyage start.
Nutritive value and essential oils characterization of Rosmarinus officinalis and Thymus capitatus from the central region of Tunisia

Rosmarinus officinalis (rosemary) and Thymus capitatus (thyme) leaves and twigs were collected from the central region of Tunisia in March and April 2008. Samples were immediately stored at –10°C. Chemical composition and in vitro gas production parameters were determined. Essential oils (EO) from the two species were extracted by steam distillation and analyzed using gas chromatography (FID), followed by a Carbon-13 NMR spectroscopy procedure to confirm the major compound structures. Rosemary and thyme were both low in crude protein (58 and 88 g/kg DM, respectively). The ADF content was similar and close 313 g/kg DM in both plant species, whereas the lignin content in thyme was higher than in rosemary (226 and 167 g/kg DM, respectively). Rosemary showed lower in vitro asymptotic gas production than thyme (27.7 vs 49.6 ml). In vitro organic matter digestibility after 24 h of incubation (IVOMD24h) and metabolisable energy (ME) estimated from the chemical composition and gas production followed a similar pattern than that of in vitro fermentation parameters. Extracted EO content in rosemary was approximatively the double of that determined in thyme (0.43 and 0.25% of DM, respectively). Thyme EO was found to be high in the active monoterpen phenol carvacrol (70%), which is the chemotype of thyme. Other secondary compounds detected in thyme were β-caryophyllen (8.5%), γ-terpinen (4.3%) and p-cymen (3.8%). On the other hand, major compounds identified in rosemary EO were 1-8 cineol (44.2%), camphor (12%) and α-pinen (11.6%). It was concluded that both native medicinal plant species would be of low nutritive value if pastured by sheep and/or goat. The EO chemotypes detected, mainly carvacrol and 1-8 cineol could be envisaged as potential additives to manipulate rumen fermentation to improve feed efficiency in ruminants and/or as a chemical tracers for trazability of meat produced from grazing sheep and goat.
Study on physiological tremor recognition algorithm in the vascular interventional surgical robot

With the development of surgical robotic technology, more and more requirements on safety property were raised upon the surgical robots. For master-slave control surgical robots, it's physiological hand tremor that influences the accuracy and success rate of the robot-assisted surgery. Focusing on the physiological tremor recognition and cancelling, this paper proposes a moving-window-least-square-support-vector-machine-based recognition algorithm and adaptive filter method to rectify the wrong operations caused by physiological tremor. The performance assessment was shown with the indicator of accuracy, which implies that the MWLSSVMAF reduces accuracy error of the tremor signal. The comparison between recognition results and surface electromyographic signal is conducted for assessing the classification accuracy rate. Also, some experiments on correction effects are carried out. The results indicate that the method proposed by our research possesses better classifying accuracy rate of 83% and that the secure property requests of vascular interventional surgical robot have been improved obviously.