Miracle-dz/UniFAR-FTUs huggingface dataset:
Our Results of Laparoscopic Totally Extraperitoneal Repair from a Single Center: The Learning Curve and Difficulties

42 Abuoğlu, Laparoscopic Inguinal Hernia Repair / doi: 10.14744/hnhj.2018. 50490 derwent laparoscopic TEP repair for an inguinal hernia were evaluated using hospital data processing system and patient files. All patients had symptomatic unilateral or bilateral inguinal hernias. Laparoscopic TEP method was used in all patients and operations were performed using 1, 10mm, 2, 5 mm trocars, and laparoscopic hand tools, and also 10 cm×15 cm Prolene mesh was used for TEP repair in all patients. The mesh was fixed with the help of a tucker. All patients were discharged on the post-operative 1st day. Patients were searched for information about recurrence and longterm complications. Patients who could not be contacted by phone were excluded from the study. The patients were examined in two groups according to their operation dates: As Group 1 (G1) (January 1, 2010–December 31, 2012); Group 2 (G2) (January 1, 2013–December 31, 2016). Demographic characteristics, operative findings, duration of operation (using intraoperative anesthesia follow-up forms), duration of hospitalization, and follow-up period, recurrence and other complications (bleeding, seroma, hematoma, wound infection, and chronic pain) were also recorded. In statistical analysis, descriptive statistics were used to define continuous variables (mean, standard deviation, minimum, median, and maximum). For the comparison of two independent continuous variables with normal distribution, Student’s t-test, and for those with non-normal distribution Mann–Whitney U-test were used. Chi-square (or Fisher Exact test where appropriate) was used to examine the relationship between categorical variables. The level of statistical significance was determined as 0.05. The analyses were performed using the Med Calc Statistical Software version 12.7. 7 (MedCalc Software bvba, Ostend, Belgium; http://www.medcalc.org; 2013).
ESTIMATING A MONETARY POLICY REACTION FUNCTION

This paper specifies and estimates a hybrid monetary policy base reaction function for the Dominican Republic (DR). The estimated reactions suggest that the Central Bank has been biased towards targeting the gap between the parallel and official exchange rates, apparently doing so in a more systematic fashion after the mid 1980s. Remarkably, these findings are in line with the Central Bank’s long-standing endorsement of a multiple exchange rate regime, and could imply a process of learning, given the monetary authorities’ preferences. JEL Classification: E52, E58, F41
Experimental and numerical study of a high-pressure waterjet

High-pressure waterjet (HPWJ) nozzles are used for cutting or for surface treatment such as cleaning, decoating and deburring. The flow within a HPWJ nozzle is compressible and turbulent due to the high water pressure and velocity. Depending on flow velocity and the geometry of the HPWJ nozzle a multiphase flow of liquid and vapor can occur. Outside of the nozzle, a highly complex turbulent waterjet breakup takes place. In order to increase the breakup length of the waterjet, geometric modifications inside the nozzle are required. On the other hand, wear resistance of a nozzle is highly desirable. In this study, the flow inside of a convergent waterjet nozzle was investigated by means of computational fluid dynamics. For the true geometrical model, μ-CT scans of the studied nozzle were used. A reverse engineering process provided the model of the nozzle. The diameter of the orifice was 0.5 mm and the inlet pressure was at 75 MPa. For the modeling of the multiphase flow, the Volume-of-Fluid (VOF) method was applied. Turbulence is also a major influential factor on the primary breakup and therefore the LargeEddy-Simulation (LES) method was utilized. Since LES method requires good inlet boundary conditions for producing stochastic components of the velocity field, separate Reynolds-Averaged-Navier-Stokes (RANS) simulations for realistic inlet conditions were performed. The studied nozzle had a flow grid, which is located in front of the convergent part of the nozzle. The influence of the flow grid on the waterjet was investigated both in the simulation and in the experiment. To validate the simulations, the flow rates from the experiment were compared with the simulation. High-speed photography provided the spray angle of the waterjet. The results of this study showed that higher turbulence, which was produced by the cross-shaped flow grid, had a stabilizing influence on the primary breakup of the jet.
ARE VERTICAL LINKAGES WITH FOREIGN FIRMS DIFFERENT? EVIDENCE FROM VIETNAM

Research on vertical linkages with foreign firms has developed along different literature strands and has often produced contradictory and incomplete findings, often as a result of too general assumptions or too aggregate data. In this study we use a unique dataset on Vietnamese foreign and domestic manufacturing firms to investigate the extent and intensity of vertical linkages between local suppliers and domestic and foreign firms inside and outside Vietnam. After controlling for a number of biases, we find that foreign firms in and outside Vietnam tend to develop more linkages with other foreign firms in the country than with domestic firms. Our analysis of the relation between linkages and productivity shows that there is potential for productivity increases for domestic firms from selling to FDI firms, but the necessary conditions need to be created for knowledge intensive linkages to develop. We identify several policy relevant characteristics that would allow for these linkages to develop.
Response surface optimization on the total phenolic content and antioxidant activities of Sabah Snake Grass ( Clinacanthus nutans ) leaves Peleg kinetic modelling extract

Sabah Snake Grass (Clinacanthus nutans) is interesting traditional medicine because of pharmacology characteristics that contain rich in phenolic content and antioxidant. The aim of study was to determine the optimum yield and exhaustive time extraction using Peleg’s model. Qualitative and quantification test for detection of orientin and vitexin using method of high performance liquid chromatography (HPLC). Based on the results obtained, the optimum concentration for orientin (0.72 ± 0.002 mg/g) and vitexin (2.10 ± 0.13 mg/g) were observed at 18 h of extraction (texhaustive). The optimum extraction parameters for optimum recovery of phenolic content and antioxidant activities from the leaves of Clinachantus nutans were determined using response surface methodology (RSM). The total phenolic content (TPC) was analyzed using the Folin-Ciocalteu method and antioxidant activities were evaluated through 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging activity, 2,2’-azinobis-(3ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical scavenging activity and the ferric reducing antioxidant power (FRAP) assay. A central composite rotatable design (CCRD) was employed to investigate the effects of ultrasonic frequency (X1: 25 40 kHz), temperature (X2: 40 80oC) and solid-to-liquid ratio (X3: 10 30 ml/g) on the recovery of TPC (Y1) and antioxidant activities of DPPH (Y2) and FRAP (Y3). The optimal parameter achieved based on combination of extraction parameters: X1 = 25 kHz sonication capacity, X2 = 80oC temperature and X3 = 30 g/ml of solid-liquid ratio. These optimum conditions yielded TPC of (25.09 mg GAE/g), DPPH (66.85%), and FRAP (9.44 μmol TE/g). The optimum values of TPC and DPPH from this study are comparable with green tea (benchmark). Our results revealed that distilled water may be a good choice for extracting antioxidant activity of Clinacanthus mutans. Concentration of orientin and vitexin compounds were extracted during optimization exhibited lower than the finding from Peleg model. Prolonged extraction at high temperature during optimization may degrade flavonoid and phenolic acid compounds. However, the concentration of extracted compound (orientin and vitexin) from the optimum parameters had produced high in phenolic content and antioxidant activity. In conclusion, the application of Peleg model was able to determine the extraction exhaustive time at the maximum extract yield. In addition, this study proved that the application both models (RSM and Peleg) have been successfully be able to provide the optimum extraction parameters with high total phenolic content and antioxidant activity.
Is This an Effective Way to Annotate Irony Activators?

In this article we describe the ﬁrst steps of the annotation process of speciﬁc irony activators in TWITTIR ` O - UD , a treebank of Italian tweets annotated with ﬁne-grained labels for irony on one hand, and according to the Universal Dependencies scheme on the other. We discuss in particular the annotation scheme adopted to identify irony activators and some of the issues emerged during the ﬁrst annotation phase. This helped us in the design of the guidelines and allowed us to draw future research directions.
Large-eddy simulation of turbulent cavitating flow in a Diesel injector including needle movement, in OpenFOAM

In this work the turbulent cavitating flow, inside a five-hole common rail Diesel injector and the effect of cavitation on erosion is investigated for the opening cycle of the injection. An explicit density-based solver of the compressible Navier-Stokes (NS) equations of the Arbitrary Lagrangian–Eulerian (ALE) formulation, suitable for cavitating flows is implemented in the open-source CFD code OpenFOAM. Numerical fluxes are calculated based on the hybrid approximate Riemann solver. The hybrid scheme provides a Mach number consistent numerical flux, suitable for subsonic up to supersonic flow conditions. Finite Volume (FV) discretization is employed in conjunction with a fourth order Runge-Kutta time integration scheme. The thermodynamic closure is based on a barotropic Equation of State (EoS) for the liquid and vapour phases. The cavitation model is based on a thermodynamic equilibrium assumption and the compressibilities of the liquid and the liquid-vapor mixture are taken into account. The injector needle movement is represented by a cell-based mesh deformation method to ensure mass conservation which accounts for the Space Conservation Law (SCL). This work focuses on potential erosion and on the development vortical structures. First, the potential erosion regions are predicted though three different indexes, the maximum collapse pressures and the erosion damage model. The latter is coupled with the CFD code. The three indexes are compared with experimental results, from CT scans. The structure of the flow is analysed with an emphasis on the interaction between coherent vortical structures and cavitation. The Wall Adapting Local Eddy viscosity (WALE) LES model was used to predict incipient and developed cavitation, while also capturing the shear layer instability, vortex shedding and cavitating vortex formation. The analysis of the turbulent flow field reveals that the opening phase of the injection event consists of four different stages. Initially a negative mass flow rate is observed, followed by a second stage characterized by a complex vortical cavitation in the sac. String cavitation in the orifice is observed during the third stage. At the last stage the cavitation region in the orifice exhibits coherent cavitation structures both in the axial line as sting cavitation and on the orifice surface as shear induced cavitation. Violent collapse events of cavitation structures are detected during the opening phase. Moreover, this work revealed the formation of thin and thick string cavitation in the orifice volume and the effects on the flow pattern in the orifice and at the exit of the orifice.
Inbreeding depression in crosses of coerulea clones of Walker’s Cattleya (Cattleya

Orchids are among the most beautiful flowers and endangered due to habitat destruction and overcollection. Cattleya walkeriana is one of the most beautiful flowers joining the small sized plant with medium large and heavily scented flowers. It is widely known and appreciated by its beautiful clones and it has much to offer to breeders because their plants have besides other attributes as small habit and big flowers, many colour variations, form and precocity, becoming flower only four years in ex vitro culture. However, in some of the original places it is becoming a red listed species. Notwithstanding, very little is known about the genetics of these flowers and the variability in the species that is widespread in the Brazilian territory. The aim of this work was to estimate the variability among cultivated materials using the F statistics and to verify if there was inbreeding in plant crosses with similar characteristics, employing as a tool the RAPD simple methodology. The results obtained showed that RAPD was good enough to estimate the variability in C. walkeriana. The selected primers were able to define colour group, especially the coerulea. Inbreeding will occur in crosses of clones with the same colour.
Automatic Segmentation of Optic Disc and Cup in Retinal Fundus Images Using Improved Two-Layer Level Set Method

Glaucoma is a group of eye conditions, which can seriously damage optic nerves because of an elevated intraocular pressure. Nowadays, glaucoma has become one of the principal causes of blindness that results in irreversible visual loss. Early screening and treatment of glaucoma can prevent further progression of optic nerve degeneration effectively. The vertical cup-to-disc ratio (CDR) is a commonly used measurement for the detection of glaucoma, and therefore accurate segmentation of optic disc (OD) and optic cup (OC) regions in retinal fundus images is of great significance. In this paper, we present a prior shape constraint-based two-layer level set method for OD and OC segmentation in fundus images. This method uses two different layers of one level set function to represent the OD and OC boundaries. In this method, the distance regularized term is designed to guarantee that the distance between the OD and OC varies smoothly. By introducing the prior shape constraint term energy, the final segmentation results of OD and OC are always in the shape of approximate ellipses. In addition, the proposed method has the property of dealing with the intensity inhomogeneity of fundus images through the local fitting energy embedded. Experiments on images from the Baidu Research database demonstrate that the proposed method has superior performance in terms of accuracy and effectiveness.
Agricultural networks across EU: What are the key features to enhance farmers' ability to learn and to innovate in cooperation with other actors?

Multi-actors networks are increasingly used by farmers to link between them and to be interactively connected with other partners, such as advisory organizations, local governments, universities, and non-farm organizations. Given the importance assigned to the agricultural innovation by EU resorting to the networking between the research chain actors and the farmers, a strong focus on enhancing the creation of learning and innovation networks is expected. In this context is relevant to have information about the features of such networks enhance farmers’ ability to learn and to innovate in cooperation with other actors. The main goal of the paper is to contribute to the understanding of which are the features of agricultural or rural networks showing determinant to enhance the farmers' ability to learn and to innovate in cooperation with other actors, namely by identifying the influencing factors encouraging the farmers’ enrolment and the influence of network stability. The additional goal of the paper is to provide insights on the way these networks link to R&D infrastructures and advisory services. Five case studies were conducted in Italy, Germany, Portugal, and UK comprising heterogeneous networks. The results highlight aspects that show decisive for the networks ability to provide effective learning and innovation platforms, including bottom-up functioning, informality, leadership and power balance, along with the participation of facilitators when networks are large and heterogeneous. These networks focus on innovation exploitation and depend on the existence of a support subsystem, namely a functioning R&D and advisory services infrastructure. They can fill in gaps in this infrastructure, but they cannot replace it.
Reduction of Harmonics in Multilevel Inverter with Non-Linear Load Using Fuzzy logic Controller

Multilevel converters are widely used in high voltage and high power applications because of their ability to generate staircase output voltage close to a sinusoidal waveform with lower harmonic distortion, higher output voltage levels and reduce switching losses with Electromagnetic Interference (EMI) problem. In this paper a new modulation technique has been introduced based on elimination of harmonic in multilevel inverter with nonlinear load by using fuzzy logic techniques. The fuzzy logic controller has been used for closed loop operation and the performance of proposed multilevel inverter has been estimated. Fundamental Switching scheme and Selective Harmonics Elimination were used to reduce the Total Harmonics Distortion (THD) value. This new technique has better effect on output voltage quality and less Total Harmonic Distortion (THD) than other modulation techniques. In order to verify the proposed modulation technique, MATLAB simulations are carried out for an inverter system.
Executive Function and Attention Performance in Children with ADHD: Effects of Medication and Comparison with Typically Developing Children

The emerging literature reports that children with Attention-Deficit/Hyperactivity Disorder (ADHD) show deficits in executive functioning. To date, the combination of drug therapy with certain evidence-based non-medication interventions has been proven to be the most effective treatment for ADHD. There is a gap in the literature regarding comparing the executive functions (EF) of treatment naïve and medicated children with ADHD with both each other and typically developing children. Altogether, 50 treatment naïve and 50 medicated children with ADHD and 50 typically developing children between the ages of six and 12 were enrolled. The Mini International Neuropsychiatric Interview for Children and Adolescents (Mini Kid) and the Test of Attentional Performance for Children (KiTAP) measures were employed. Treatment naïve children with ADHD showed weaker performance on most executive function measures (12 out of 15) than either the medicated ADHD group or the controls. There were no significant differences between the medicated ADHD children and typically developing children in most KiTAP parameters (10 out of 15). Executive function impairments were observable in treatment naïve ADHD children, which draws attention to the importance of treating ADHD. Future studies should focus on the specific effects of stimulant medication on executive functions.
A training programme for master–student counsellor interns at university counselling centre in Taiwan

The purpose of this article is to describe a four-week internship training programme (ITP) within the frame of the developmental instruction model (DIM). Despite the importance of internship in counsellor education, research related to ITP in Taiwan can hardly be found. The ITP created by the author aims to assist intern counsellors to transit from being a graduate student to a clinical practitioner of counselling. Four aspects of the DIM were employed in this programme: structure, diversity, experiential learning and personalization. Supervisors at the university counselling centres (UCCs) could use the ITP to provide structure for interns to process what they have acquired about counselling learning information. They need to pay attention to the diversity of interns, and design the training details based on the demands and characteristics of individual intern. The ITP encourages the employment of experiential learning in enhancing the interns’ integration of their observation at the UCC and their experience, reflection, conceptualization and actual practice during the internship. By creating a humane learning atmosphere and facilitating a safe learning environment, the UCC staff could reassure the interns in risk-taking and wide in-depth learning.
Weather Forecasting using Deep Feed Forward Neural Network (DFFNN) and Fuzzy Outlier Removal

-Weather forecasting is significant designed for people who facilitate to create additional informed daily decisions, and to keep out of danger. Precise Weather forecasting is becomes one of most difficult problems approximately the world. Unlike conventional methods, modern Weather forecasting consists of a combination of system models, examination. Data mining uses various technologies to forecast weather, predict rainfall, wind pressure, humidity, etc. Classification in data mining varied the restriction to view the clear information. The prediction of weather should be precise and moreover the weather be supposed to be forecasted previous at least a month before which determination be cooperative designed for many applications like agriculture, military, etc. Artificial Neural Networks (ANNs) have been applied comprehensively to together regress and classify weather experience. So in this work proposed Deep Feed Forward Neural Network (DFFNN) is rendering accurate predictions with noisy datasets, there is currently not a significant amount of research focusing on whether DFFNN are capable of producing accurate forecasts of relevant weather variables from small-scale, imperfect datasets. In addition the proposed work shows the outliers in the dataset is also removed by using fuzzy technique during the classification task. There is no important quantity of investigate focusing on the forecasting performance of Neural Networks realistic to weather datasets with the purpose of have been temporally rolled-up from a base dataset. Keywords--Data Mining, Classification, Weather M. Nagaselvi, MCA,(Mphil). , Mphil Scholar, Sri Ramakrishna College of Arts and Science, Coimbatore-641044. E-mail:nagaselvi11@gmail.com Dr.T. Deepa, Msc, MBA, Mphil, Phd, Sri Ramakrishna College of Arts and Science, Coimbatore-641044 Forecasting, Classification Methods, Soft Computing, Artificial Neural Network (ANN), Deep Feed Forward Neural Network (DFFNN) and Fuzzy Outlier Removal
University of Groningen A Critical Assessment of a Method for Detecting Diachronic Meaning Shifts Haagsma, Hessel; Nissim, Malvina

Automatically detecting shifts of meaning over time is desirable for Natural Language Processing tasks as well as research in the Digital Humanities. We train diachronic word embeddings on Dutch newspaper data and compare representations of the same terms from different times to each other. The aim is verifying whether such comparison can highlight the emergence of a new (figurative) meaning for a given term. The most interesting outcome of this experiment is methodological: while in some cases we observe that this method is efficient, as it has been shown to be in previous work on Italian, we also observe that in many other cases results are not what we would expect. This leads us to an in-depth analysis of interfering aspects and to a discussion of methodological choices, towards the development of what we believe is a timely and needed roadmap for developing diachronic studies on meaning shifts that rely on distributed representations.
Detection of Suspicious Tissue Lesions

RS based discrimination of diseased tissues from normal surroundings will facilitate diagnosis and treatment of precancers before malignant manifestations as see-and-treat procedures. In front of this aim, two RS setups were constructed suiting clinical application in dermatology and gynecology departments. Patients or patient materials were measured by RS, and Raman spectra were processed prior to spatial classification of spectra in correlation with the histolopathological findings.