Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust approach for people counting in dense crowd images using deep neural networks

People counting in dense crowd images with deep neural networks are proved to be effective. The models like RCNN are able to predict the crowd count by head detection, using the CNN and selective search algorithm, but these approaches are very slow, as they involve computing convolutional operation for 2k regional proposals, involving no shared computations, besides the selective search algorithm itself is slow. In this approach a Faster R-CNN for head detection which uses a Regional Proposal Network (RPN) has been used. The region proposal network is a Fully Convolutional Neural Networks that generates region proposals, these regional proposal were fed in to RoI pooling layer and subsequently classified and localized, Thus Faster-RCNN reduces computation cost of convolutional operations by passing a image only once, sharing the convolutional operations and also using RPN for regional Proposals. Using the Faster R-CNN MAE and MSE are reduced compared to R-CNN.
Formation and deposition of polymer nanostructures on surfaces

In this thesis different routes to the formation of extended two-dimensional polymers via on-surface coupling reactions are presented. Polyphenylene networks formed by the molecules tri-(bromo-phenyl)-benzene via on-surface Ullmann coupling reactions are investigated with scanning tunnelling microscopy. The polyphenylene networks with near complete surface coverage exhibit a vitreous structure. The network is composed of linked molecules forming polygons with four to eight edges. A different set of covalently bound molecular nanostructures can be formed on a surface upon thermal activation of porphyrin building blocks. Porphyrin molecules are covalently linked to form one dimensional chains or extended networks using either Ullmann-type coupling reactions to link brominated phenyl sidegroups, or Glaser-Hay-type coupling to form butadiene links via reaction of two phenyl-ethylene sidegroups. The resulting polymers are investigated with scanning tunnelling microscopy and Raman spectroscopy. In a complementary strand of research it is shown that thin films of C60 can promote adhesion between a gold thin film deposited on mica and a solution-deposited layer of the elastomer polymethyldisolaxane (PDMS). This molecular adhesion facilitates the removal of the gold film from the mica support by peeling and provides a new approach to template stripping which avoids the use of conventional adhesive layers. The fullerene adhesion layers may also be used to remove organic monolayers and thin films as well as two-dimensional polymers such as the porphyrin networks discussed previously. Following the removal from the mica support the monolayers may be isolated and transferred to a dielectric surface by etching of the gold thin film, mechanical transfer and removal of the fullerene layer by annealing/dissolution. The use of this molecular adhesive layer provides a new route to transfer polymeric films from metal substrates to other surfaces. A different set of experiments investigated porphyrin nanorings and their interaction with C60 on a gold surface. Solvent-induced aggregates of nanoring cyclic polymers may be transferred by electrospray deposition to a surface where they adsorb as three dimensional columnar stacks. The observed stack height varies from single rings to three stacked rings. Those stacked layers of cyclic porphyrin nanorings constitute nanoscale receptacles with variable height and diameter which preferentially adsorb sublimed C60 molecules. Using scanning tunnelling microscopy the filling capacity of these nanoring traps is determined, as is the dependence of adsorbate capture on stack height and diameter.
An open computing language‐based parallel Brute Force algorithm for formal concept analysis on heterogeneous architectures

Algorithms for the extraction of formal concepts are widely studied in several areas of knowledge, such as finance, health, and statistics. However, these algorithms require high‐performance processing due to their combinatorial characteristics. In this work, an Open computing language (OpenCL)‐based Brute Force algorithm is proposed and evaluated for formal concept extraction on heterogeneous architectures (CPU+GPU and CPU+FPGA). The CPU+GPU architecture presents higher performance and scalability than other architectures when our Brute Force algorithm processes high dimensional contexts with many objects and attributes. Our parallel approach shows performance results up to 18× better than a smarter sequential algorithm called Data‐Peeler. Moreover, our Brute Force algorithm running on CPU+GPU architecture has greater energy efficiency, reaching at least 1.79× more operations per energy consumption than other algorithms on different architectures explored in this work.
The Role of Fluids in the 2008 Ms8.0 Wenchuan Earthquake, China

Fluid intrusions into seismic zones play a fundamental role in the initiation of earthquakes and rupture processes, yet the mechanisms that control these interactions are enigmatic and widely debated. Here, we present a series of signatures for new seismic velocities (Vp, Vs) and Vp/Vs ratio imaging and stress simulations that reveal the impact of fluids, including partial melting, on the seismogenesis of the 2008 Wenchuan earthquake that occurred on the eastern Tibetan Plateau. We found that a prominent low‐V and high‐Vp/Vs body under the western side of the 2008 Wenchuan hypocenter and two gaps characterized by low‐V and high‐Vp/Vs inserted into its rupture process were clearly imaged. One of these gaps terminated the southwestward coseismic slip while the other weakened the northeastern rupture process. We interpreted both of these bodies as the result of fluid penetration associated with partial melting of the ductile flow from the lower crust of Tibet. Such ductile materials were pushed against the rigid basement of the Yangtze craton and accumulated there, maintaining high pore pressure. We presume that a system such as this, with high pore pressure and fluids in the fluid‐pressurized regime, might have reduced the threshold for fault failure, transformed this zone into a potential fault risk front, and thus increased the likelihood of failure of the mainshock fault. We speculate that fluids invading the seismogenic layer of the Longmen‐Shan fault zone played a crucial role in the initiation of the 2008 Wenchuan earthquake and its rupture process.
Valuing Dynamic Capabilities-Based Synergies with Real Options

Acquisition-based dynamic capabilities have become well established as a new imperative for organizing mergers and acquisitions (M&A) processes. However, understanding the full benefits and possible limits of real options applications to measure a dynamic capability-based synergy in M&A deals remains a challenge. This paper draws on real options theory to explore some of these benefits and limits to value a synergy in two highly strategic M&A deals. More specifically, the author develops the proposition that justifies the role of dynamic capabilities as antecedents of the success of M&A deals in the information and communications technology industry and demonstrates real options application to measure M&A synergies.
Monte-Carlo Study of Ion-Sputtering Parameters and Ab-Initio Calculations of Selected Perovskites for Solar-Powered Electricity

Attributable to efficiencies as high as 25.2%, organic inorganic hybrid perovskite has become the quickest developing solartechnology, rivalling the conventional photovoltaic technology. Although, they are unique and remarkable, stability concern and toxic behaviour of perovskites impedemass production. With this impetusofrealizing a non-toxic perovskite, a new approach was proposed by performing Monte Carlo simulations. In this paper, this approach was further studied with an First principlesinvestigations using the plane-wave pseudopotential method within the density functional theory (DFT) as employed in Quantum ESPRESSO (QE) software package. Mechanical and electronic properties of CH3NH3PbBr3, CH3NH3SnBr3, CH3NH3SnI3, and CH3NH3PbI3, perovskites were investigated. Lattice constants were calculated to understand the mechanical properties, while band gaps were calculated to shed more light on their electronic properties. Our resultswere compared with the experimental and theoretical values and found a good agreement between them. These indicated that the two materials were remarkably similar and that Sn was a good substitute for Pb in solar cell perovskite materials.
Managers’ Competences in Private Hospitals for Investment Decisions during the COVID-19 Pandemic

The COVID-19 pandemic has posed an unprecedented challenge for health systems worldwide. The increased demand for investment in hospitals has become one of the greatest financial vulnerabilities, and in this context, the manager’s involvement in decision-making is associated with better analysis in order to achieve better results. This article aims to define a model to outline the manager profile in private hospitals, as well as the process and the relationship with investment decision-making, so as to guide future work to improve institutions’ performance and ensure the sustainability of patient care processes and the use of resources. Semi-structured interviews were held with an administrative (or financial) director in Brazil, Canada and Portugal and analyzed by the conventional content analysis method and coded, using NVivo 11, identifying the main topics. A model for investment decision-making is proposed to improve resource allocation and performance. The results indicate, for multidisciplinary training, where managers contribute to an efficient use of resources and contribute to the maintenance of quality of care, including about investment and financing of hospitals, where performance analysis reflects on decision-making.
Minimum Wages, Relative Wages, and Productivity: An Empirical Analysis on Indonesia Food and Beverage Industry

Background of the research: Previous study on minimum wages policy in Indonesia mostly focused on employment and welfare effect, while its relationship with productivity is lack. Purpose: This study tends to study the wages and productivity relationship using minimum wages increase information in Indonesia. This paper aims to calculate the time varying productivity using one step production function then implements difference-in-difference technique to measure the productivity changes due to the implementation of minimum wages policy. Methodologies: We choose the case of food and beverage industry in Indonesia and find a strong support for efficiency wages theory. This research takes information from medium to large firms within food and beverages industry in several region in Indonesia as a sample. The reason why this research used this sample is the importance of food and beverages industry in Indonesian economy. Principal results: Using standard panel regression, this paper also find evidence on positive relationship between relative wages and productivity. Major conclusions: The findings showed that firms adopting minimum wages policy show higher changes in productivity compared to firm that is already above the minimum wages. Contributions to the field: the study made a good attempt to examine a critical issue of relationship between minimum wage policy and total factor productivity changes for food industry in the context of Indonesia. Important aspects of the study: The important aspects of the study lie in the analysis of food demand as the indicator of agricultural markets.
Parental Migration and Risk of Sexual Assault Against Children in Rural China

This study investigates the difference in rates of sexual assault between left-behind children and those living with both parents in rural China and attempts to identify potential social mechanisms explaining this variation. Using data from a probability sample of middle school students in Guizhou Province, China, our study reveals that parental migration, particularly maternal and both-parent migration, significantly increases children’s risk of sexual victimization. This relationship is mediated by three intervening pathways: weakened caretaker monitoring and supervision, children’s increased engagement in risky lifestyles, and elevated exposure to general victimization. These findings highlight the urgency to develop prevention and treatment programs based on a holistic understanding of protective and risk factors for sexual abuse against left-behind children in rural China.
Design and Implementation of Waste Reduction Intelligent Cafeteria System Based on Raspberry Pi

With the development of higher education in China, the number of college students on campus is increasing, and the number of people eating in college cafeterias also increases. On the one hand, the problem of crowded lines in school cafeterias during peak dining periods is becoming more and more serious, and students have a poor dining experience. On the other hand, it is often difficult to establish an effective communication mechanism between students and cafeterias. The traditional canteen model is difficult to meet the current needs, and the upgrade of the canteen system in universities is urgent. This paper designs a set of waste reduction intelligent cafeteria system based on Raspberry Pi to reduce waste. The whole system effectively solves the problems of traditional canteens, and establishes a certain reward mechanism to encourage students to use up the purchased dishes and reduce waste. The university canteen provides a practical model for improving service quality and reform and transformation.
Hydatid Cysts of the Liver Rupture into the Peritoneal Cavity: Fifteen Cases and Review of the Literature

BackgroundHydatid cyst is a parasitic infection caused mainly by E. Granulosus, which is generally considered benign. However, the hepatic Hydatid Cyst rupture in the abdominal cavity is a life-threatening incident that requires urgent and multidisciplinary management (emergency physician, radiologists, anesthetists, and surgeons). This study describes clinical and paraclinical liver hydatid cyst rupture in the peritoneal cavity and details the appropriate treatment.Materials and MethodsFifteen liver hydatid cyst cases ruptured into the abdominal cavity that underwent urgent surgery were collected over eight years. Results There were nine men and six women. Patients' age ranged from 14 to 59 years, with an age average of 38 years. Two patients were admitted with abdominal trauma, and acute abdominal pain was the common consultation's reason. Only one patient had an anaphylactic shock. Both abdominal ultrasound and CT scan showed discontinuous cyst wall and intraperitoneal fluid in 100% of cases. Intraoperatively, the intraperitoneal effusion was clear in thirteen cases and purulent in two. All patients underwent unroofing procedure associated with intra-operative peritoneal lavage and external drainage. The mean hospital stay was 6.11 days, and the mean follow-up was 19 months. No case of recurrence was reported among the patients.ConclusionRupture of a hydatid cyst in the abdominal cavity should be evoked in front of acute abdominal pain, especially in endemic areas, and in the presence of an allergic reaction or anaphylactic shock signs. Combined surgical and medical care starting in the emergency room is the only guarantee of a good outcome.
The frequency exponent of artificial sandstone's complex resistivity spectrum

The complex resistivity spectra of 16 artificial sandstone samples with different physical property at different water and solution saturations were measured and fitted with the Cole–Cole model in the frequency band of 40 Hz to 110 MHz. The frequency exponent in the model indicates the ideal degree of the sample's capacitive property. The experimental result shows that the frequency exponents of the samples are concentrated mainly between 0.82 and 0.88 and present a segmented law that decreases first and then increases with decreasing the water saturation. The minimum frequency exponent has a linear relationship with porosity and cementation index and an exponential relationship with formation factors. The frequency exponent is expected to be used in the study of the oil–water distribution in the reservoir. The frequency exponents of the samples decrease with an increase in clay content. Frequency exponents are independent of the ion type in the solution. Numerical simulation results support that the capacitive property generated by the connected pore‐throat spaces is near ideal, but the capacitive property contributed by the closed pore‐throat spaces is non‐ideal. This could be the possible reason why the frequency exponents of the samples are less than one. The pore‐throats with higher capillary pressure can be blocked and become secondary closed pore‐throat space during the flooding process and result in a decrease in frequency exponent. This can explain the influence of reservoir parameters on frequency exponent and can further clarify the physical significance of the Cole–Cole frequency exponent on the rock's complex resistivity.
Biocatalytic Transformation of 5-Hydroxymethylfurfural into 2,5-di(hydroxymethyl)furan by a Newly Isolated Fusarium striatum Strain

The compound 2,5-di(hydroxymethyl)furan (DHMF) is a high-value chemical block that can be synthesized from 5-hydroxymethylfurfural (HMF), a platform chemical that results from the dehydration of biomass-derived carbohydrates. In this work, the HMF biotransformation capability of different Fusarium species was evaluated, and F. striatum was selected to produce DHMF. The effects of the inoculum size, glucose concentration and pH of the media over DHMF production were evaluated by a 23 factorial design. A substrate feeding approach was found suitable to overcome the toxicity effect of HMF towards the cells when added at high concentrations (>75 mM). The process was successfully scaled-up at bioreactor scale (1.3 L working volume) with excellent DHMF production yields (95%) and selectivity (98%). DHMF was purified from the reaction media with high recovery and purity by organic solvent extraction with ethyl acetate.
Student Performance Prediction Based on a Framework of Teacher’s Features

Teachers teaching skills are essential to motivate students’ engagement in online educational environments, where students and teachers interact with each other, generating a large amount of educational data. However, to the best of our knowledge, there is no previous study that takes advantage of the huge quantity of teachers’ behavioral data to predict students’ performance. To fill this research gap, we elaborated a theoretically based framework of teacher’s characteristics, that guided an automatic data collection of teachers’ behaviors to predict students’ performance. The implementation of a computational prediction system applied the Random Forest classifying algorithm, which achieved better performance, according to AUC metric, when compared to other algorithms. Two exploratory case studies were conducted to investigate the efficiency and efficacy of the framework of teacher’s features in Goiás Judicial School EJUG teachers in Brazil. The results from the case studies shown that the framework is effective to predict students’ performance. This work contributes to distant education, enabling monitoring teachers’ actions aiming students’ academic best achievements.
Processing Bio-Argo nitrate concentration at the DAC Level

The only method used to date to measure dissolved nitrate concentration (NITRATE) with sensors mounted on profiling floats is based on the absorption of light at ultraviolet wavelengths by nitrate ion (Johnson and Coletti, 2002; Johnson et al., 2010; 2013; D’Ortenzio et al., 2012). Nitrate has a modest UV absorption band with a peak near 210 nm, which overlaps with the stronger absorption band of bromide, which has a peak near 200 nm. In addition, there is a much weaker absorption due to dissolved organic matter and light scattering by particles (Ogura and Hanya, 1966). The UV spectrum thus consists of three components, bromide, nitrate and a background due to organics and particles. The background also includes thermal effects on the instrument and slow drift. All of these latter effects (organics, particles, thermal effects and drift) tend to be smooth spectra that combine to form an absorption spectrum that is linear in wavelength over relatively short wavelength spans. If the light absorption spectrum is measured in the wavelength range around 217 to 240 nm (the exact range is a bit of a decision by the operator), then the nitrate concentration can be determined. Two different instruments based on the same optical principles are in use for this purpose. The In Situ Ultraviolet Spectrophotometer (ISUS) built at MBARI or at Satlantic has been mounted inside the pressure hull of a Teledyne/Webb Research APEX and NKE Provor profiling floats and the optics penetrate through the upper end cap into the water. The Satlantic Submersible Ultraviolet Nitrate Analyzer (SUNA) is placed on the outside of APEX, Provor, and Navis profiling floats in its own pressure housing and is connected to the float through an underwater cable that provides power and communications. Power, communications between the float controller and the sensor, and data processing requirements are essentially the same for both ISUS and SUNA.
DCGAN-generated Synthetic Images Effect on White Blood Cell Classification

White blood cell can give information about someone’s health. Imbalanced amount of white blood cells indicates someone’s disease. The disease detection using white blood cell can be done by using flow cytometry, however the use of the device has many drawbacks. The drawbacks can be solved by using computer aided classification. However, another problem arises, that the available white blood cell dataset has small dataset and the class distribution is imbalanced. This problem can be solved by using classic data augmentation and DCGAN to create synthetic image in order to balance the amount of white blood cell dataset. The balanced dataset then trained using ResNet50 model as the classification model. Accuracy, precision, recall and Fl-score are used as the performance measures of the classification. The result shows that the model obtain accuracy of 82.5%. ResNet50 was chosen because it can produce good accuracy when used in medical image classification.
A Context-free Grammar based Association Rule Mining Technique for Network Dataset

Among various data mining concepts like prediction, clustering, classification, association and outlier discovery, association is a useful technique to extract the interesting relations among data items effectively. Association technique is applied in a number of applications like marketing, education, chemical, bioinformatics, computational linguistics and etc. The important purpose of association is to provide useful information of buying preferences of customers in supermarket in order to increase the sales opportunity, which is called as market- basket analysis. Till now there are many algorithms were developed, but the usage of formal grammars in association rule mining (ARM) is a latest technique to mine required data by means of grammars. In this paper ARM is performed using Context –free Grammar (CFG) – (ARM – Grammar) and the experiments are conducted on MATLAB 2017 software using network dataset, KDDCUP’99. Experimental outcomes prove that the proposed ARM – Grammar is effective than the traditional ARM approach.