Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of layer thickness on mechanical properties in stereolithography

Purpose – Mechanical properties such as tensile, yield, impact strengths, and development of residual stresses play an important role intooling applications. The objective of this paper is to investigate the effect of layer thickness – one of the influential process parameters in stereolithography (SL) process, on mechanical properties of SL components.Design/methodology/approach – Test specimens are constructed as per the ASTM standards for different layer thicknesses in SL 5000 machine, using epoxy resin CIBA tool ® SL5530, a high temperature resistant SL material that is suitable for rapid tooling applications. Tensile, yield and impact tests are carried out with suitable equipments. Residual stress is analysed using hole drill method.Findings – The analysis reveals that when the layer thickness is smaller, the strength of the part is higher.Research limitations/implications – Conclusion of this research is drawn based on the analysis of the most widely used three layer thicknesses of 100, 125 and 150 .
Enhancing innovation quality through the involvement of external partners: An explorative analysis on the bio-pharmaceutical industry

The work suggests a methodological framework to detect information about innovation practices and their effects in terms of innovation quality from patent data. In this explorative analysis on the bio-pharmaceutical industry, three innovation practices are investigated: internal development, R&D outsourcing and joint development. Four quality indicators are taken into account: novelty level, originality of the technological combination, technological acknowledgment and internal value. Moreover, the effect on exploitation vs. exploration strategies is evaluated. The framework is tested on a sample of 460 patents. Results show that the involvement of external partners enhances the technological acknowledgement of patented technologies. R&D outsourcing is employed to allow companies to specialize in their core technical field, whereas joint development is used to generate new knowledge architectures.
Fair Allocation of Indivisible Public Goods

We consider the problem of fairly allocating indivisible public goods. We model the public goods as elements with feasibility constraints on what subsets of elements can be chosen, and assume that agents have additive utilities across elements. Our model generalizes existing frameworks such as fair public decision making and participatory budgeting. We study a groupwise fairness notion called the core, which generalizes well-studied notions of proportionality and Pareto efficiency, and requires that each subset of agents must receive an outcome that is fair relative to its size. In contrast to the case of divisible public goods (where fractional allocations are permitted), the core is not guaranteed to exist when allocating indivisible public goods. Our primary contributions are the notion of an additive approximation to the core (with a tiny multiplicative loss), and polynomial time algorithms that achieve a small additive approximation, where the additive factor is relative to the largest utility of an agent for an element. If the feasibility constraints define a matroid, we show an additive approximation of 2. A similar approach yields a constant additive bound when the feasibility constraints define a matching. For feasibility constraints defining an arbitrary packing polytope with mild restrictions, we show an additive guarantee that is logarithmic in the width of the polytope. Our algorithms are based on the convex program for maximizing the Nash social welfare, but differ significantly from previous work in how it is used. As far as we are aware, our work is the first to approximate the core in indivisible settings.
Locomotion efficiency optimization of biologically inspired snake robots

Snake robots constitute bio-inspired solutions that have been studied due to their ability to move in challenging environments where other types of robots, such as wheeled or legged robots, usually fail. In this paper, we consider both land-based and swimming snake robots. One of the principal concerns of the bio-inspired snake robots is to increase the motion efficiency in terms of the forward speed by improving the locomotion methods. Furthermore, energy efficiency becomes a crucial challenge for this type of robots due to the importance of long-term autonomy of these systems. In this paper, we take into account both the minimization of the power consumption and the maximization of the achieved forward velocity in order to investigate the optimal gait parameters for bio-inspired snake robots using lateral undulation and eel-like motion patterns. We furthermore consider possible negative work effects in the calculation of average power consumption of underwater snake robots. To solve the multi-objective optimization problem, we propose transforming the two objective functions into a single one using a weighted-sum method. For different set of weight factors, Particle Swarm Optimization is applied and a set of optimal points is consequently obtained. Pareto fronts or trade-off curves are illustrated for both land-based and swimming snake robots with different numbers of links. Pareto fronts represent trade-offs between the objective functions. For example, how increasing the forward velocity results in increasing power consumption. Therefore, these curves are a very useful tool for the control and design of snake robots. The trade-off curve thus constitutes a very useful tool for both the control and design of bio-inspired snake robots. In particular, the operators or designers of bio-inspired snake robots can choose a Pareto optimal point based on the trade-off curve, given the preferred number of links on the robot. The optimal gait parameters for the robot control system design are then directly given both for land-based and underwater snake robots. Moreover, we are able to obtain some observations about the optimal values of the gait parameters, which provide very important insights for future control design of bio-inspired snake robots.
Statistical, Spatial and Temporal Mapping of 911 Emergencies in Ecuador

A public safety answering point (PSAP) receives alerts and attends to emergencies that occur in its responsibility area. The analysis of the events related to a PSAP can give us relevant information in order to manage them and to improve the performance of the first response institutions (FRIs) associated to every PSAP. However, current emergency systems are growing dramatically in terms of information heterogeneity and the volume of attended requests. In this work, we propose a system for statistical, spatial, and temporal analysis of incidences registered in a PSAP by using simple, yet robust and compact, event representations. The selected and designed temporal analysis tools include seasonal representations and nonparametric confidence intervals (CIs), which dissociate the main seasonal components and the transients. The spatial analysis tools include a straightforward event location over Google Maps and the detection of heat zones by means of bidimensional geographic Parzen windows with automatic width control in terms of the scales and the number of events in the region of interest. Finally, statistical representations are used for jointly analyzing temporal and spatial data in terms of the “time–space slices”. We analyzed the total number of emergencies that were attended during 2014 by seven FRIs articulated in a PSAP at the Ecuadorian 911 Integrated Security Service. Characteristic weekly patterns were observed in institutions such as the police, health, and transit services, whereas annual patterns were observed in firefighter events. Spatial and spatiotemporal analysis showed some expected patterns together with nontrivial differences among different services, to be taken into account for resource management. The proposed analysis allows for a flexible analysis by combining statistical, spatial and temporal information, and it provides 911 service managers with useful and operative information.
An Ensemble Classifier with Random Projection for Predicting Protein-Protein Interactions Using Sequence and Evolutionary Information

Identifying protein-protein interactions (PPIs) is crucial to comprehend various biological processes in cells. Although high-throughput techniques generate many PPI data for various species, they are only a petty minority of the entire PPI network. Furthermore, these approaches are costly and time-consuming and have a high error rate. Therefore, it is necessary to design computational methods for efficiently detecting PPIs. In this study, a random projection ensemble classifier (RPEC) was explored to identify novel PPIs using evolutionary information contained in protein amino acid sequences. The evolutionary information was obtained from a position-specific scoring matrix (PSSM) generated from PSI-BLAST. A novel feature fusion scheme was then developed by combining discrete cosine transform (DCT), fast Fourier transform (FFT), and singular value decomposition (SVD). Finally, via the random projection ensemble classifier, the performance of the presented approach was evaluated on Yeast, Human, and H. pylori PPI datasets using 5-fold cross-validation. Our approach achieved high prediction accuracies of 95.64%, 96.59%, and 87.62%, respectively, effectively outperforming other existing methods. Generally speaking, our approach is quite promising and supplies a practical and effective method for predicting novel PPIs.
Identifying Patterns of Idea Diffusion in Innovator Networks

The diffusion of innovative ideas throughout a social network of innovators depends crucially on how people are connected and influence each other, and particularly on the advocacy of influential individuals. We contend that existing conceptualizations of innovation diffusion and peer influence do not suffice to capture the multi-faceted nature of idea diffusion. To address this challenge, we adopt concepts from both innovation management and social network analysis to identify patterns of idea diffusion. Using topology analysis and percolation analysis, we examine the impact of peer influence on the percolation of idea-related artifacts. We demonstrate the applicability of our approach using the preliminary results of our study with one of Switzerland’s major independent banking software providers. The outcome will not only have valuable contributions to the studies of innovation management and social network analysis, but also make a methodological contribution by introducing the examination of artifact percolation to study idea diffusion.
Literature Review on Feature Selection Methods for High-Dimensional Data

selection is a process of removing the redundant and the irrelevant features from a dataset to improve the performance of the machine learning algorithms. The feature selection is also known as variable selection or attribute selection. The features are also known as variables or attributes. The machine learning algorithms can be roughly classified into two categories one is supervised learning algorithm and another one is unsupervised learning algorithm. The supervised learning algorithms learn the labeled data and construct learning models that are known as classifiers. The classifiers are employed for classification or prediction to identify or predict the class-label of the unlabeled data. The unsupervised learning algorithms lean the unlabeled data and construct the learning models that known as clustering models. The clustering models are employed to cluster or categorize the given data for predicting or identifying their group or cluster. Mostly, the feature selections are employed for the supervised learning algorithms since they suffered by the high-dimensional space. Therefore, this paper presents a complete literature review on various feature selection methods for high-dimensional data.
Synthesis and Characterization of Zinc Oxide Nanowires Grown Hydrothermally on Glass Substrate

We report the synthesis of ZnO nanowires grown on glass using a two-step process: (a) preparation of the seed layer, and (b) growth of the nanostructures. First step:solutions of zinc acetate dehydrate and 1-propanol of 10 mM concentrationwere spin coated on glass at 2000 rpm for 58 s. A seed layer was obtained after three layers of spin coating. Second step: vertical ZnO nanowires were grown by dipping the substrate in a 25 mMequimolarsolution of zinc nitrate hexahydrate and hexamethylenetetramine. Subsequently, films were thermally treated with a commercial microwave oven at different power settings (350 and 700 W) for 5, 20 and 35 min. The ZnO nanowires obtained were characterized optical and morphologically. Scanning electron microscopy analysis showed that the size of ZnO nanowires was less than 50 nm in diameter and around 500 nm in length. XRD patterns revealed that when low power in the microwave oven was utilized, the presence of Zn (OH)2 on the films is observed. The ZnO nanowires bandgap energy was obtained from optical transmission spectra.
HOXC6 predicts invasion and poor survival in hepatocellular carcinoma by driving epithelial-mesenchymal transition

Aberrant expression of HOXC6 has been reported in several malignant tumors, yet little is known about the value of HOXC6 in invasion and prognosis of hepatocellular carcinoma (HCC). HOXC6 expression was positively correlated with high AFP level, liver cirrhosis, larger tumor, vascular invasion and BCLC stage. Kaplan-Meier analysis revealed that HOXC6 was an independent predictor for overall survival (OS) and time to recurrence (TTR). In addition, HOXC6 status could act as prognostic predictor in different risk subgroups. Moreover, HOXC6 maintained its prognostic value in different ability of invasiveness. Furthermore, combination of HOXC6 and serum AFP could be a potential predictor for survival in HCC patients. Additionally, further study showed that HOXC6 may promote invasion of HCC by driving epithelial-mesenchymal transition (EMT). Knockdown of HOXC6 significantly decreased the migration and invasion of HCC cells and changed the expression pattern of EMT markers. An opposite expression pattern of EMT markers was observed in HOXC6-transfected cells. In addition, immunohistochemistry and RT-PCR results further confirmed this correlation. In conclusion, HOXC6 contributes to invasion by inducing EMT pathway and predicts poor prognosis of HCC. HOXC6/AFP expression may help to distinguish the different risks of HCC patients after hepatectomy.
Insect herbivory and plant adaptation in an early successional community *

To address the role of insect herbivores in adaptation of plant populations and the persistence of selection through succession, we manipulated herbivory in a long‐term field experiment. We suppressed insects in half of 16 plots over nine years and examined the genotypic structure and chemical defense of common dandelion (Taraxacum officinale), a naturally colonizing perennial apomictic plant. Insect suppression doubled dandelion abundance in the first few years, but had negligible effects thereafter. Using microsatellite DNA markers, we genotyped >2500 plants and demonstrate that insect suppression altered the genotypic composition of plots in both sampling years. Phenotypic and genotypic estimates of defensive terpenes and phenolics from the field plots allowed us to infer phenotypic plasticity and the response of dandelion populations to insect‐mediated natural selection. The effects of insect suppression on plant chemistry were, indeed, driven both by plasticity and plant genotypic identity. In particular, di‐phenolic inositol esters were more abundant in plots exposed to herbivory (due to the genotypic composition of the plots) and were also induced in response to herbivory. This field experiment thus demonstrates evolutionary sorting of plant genotypes in response to insect herbivores that was in same direction as the plastic defensive response within genotypes.
Multi-Dueling Bandits and Their Application to Online Ranker Evaluation

Online ranker evaluation focuses on the challenge of efficiently determining, from implicit user feedback, which ranker out of a finite set of rankers is the best. It can be modeled by dueling bandits, a mathematical model for online learning under limited feedback from pairwise comparisons. Comparisons of pairs of rankers is performed by interleaving their result sets and examining which documents users click on. The dueling bandits model addresses the key issue of which pair of rankers to compare at each iteration. Methods for simultaneously comparing more than two rankers have recently been developed. However, the question of which rankers to compare at each iteration was left open. We address this question by proposing a generalization of the dueling bandits model that uses simultaneous comparisons of an unrestricted number of rankers. We evaluate our algorithm on standard large-scale online ranker evaluation datasets. Our experimentals show that the algorithm yields orders of magnitude gains in performance compared to state-of-the-art dueling bandit algorithms.
Gait stabilization of a quasi-passive walker based on energy balance by utilizing a mechanical oscillator

A control method based on energy balance was proposed for gait stabilization of a quasi-passive walker. The mechanical energy is input into the walker by a mechanical oscillator for stable walking. The target trajectory of the mechanical oscillator is determined by online planning of its period, phase and amplitude. The period is determined by the period of lateral motion of the walker based on forced entrainment, and the amplitude is determined based on energy balance. The control method was numerically examined on a changeable slope, and the results showed that the method can increase the environmental adaptability of the walker.
Wireless Powered Cooperation-Assisted Mobile Edge Computing

This paper studies a mobile edge computing (MEC) system in which two mobile devices are energized by the wireless power transfer (WPT) from an access point (AP) and they can offload part or all of their computation-intensive latency-critical tasks to the AP connected with an MEC server or an edge cloud. This harvest-then-offload protocol operates in an optimized time-division manner. To overcome the doubly near-far effect for the farther mobile device, cooperative communications in the form of relaying via the nearer mobile device is considered for offloading. Our aim is to minimize the AP’s total transmit energy subject to the constraints of the computational tasks. We illustrate that the optimization is equivalent to a min–max problem, which can be optimally solved by a two-phase method. The first phase obtains the optimal offloading decisions by solving a sum-energy-saving maximization problem for given an energy transmit power. In the second phase, the optimal minimum energy transmit power is obtained by a bisection search method. Numerical results demonstrate that the optimized MEC system utilizing cooperation has significant performance improvement over systems without cooperation.
Energy-aware task and interrupt management in Linux

As multi-core and SMP systems become more generally available, energy management needs in Linux have also become more complex. Energy management in Linux was primarily designed for interactive systems where relatively simple inactivity based strategies worked effectively for most cases. Modern enterprise class hardware needs a more complex power management strategy to save energy with the least impact on the performance of enterprise workloads. Traditionally, the Linux kernel for servers has been optimized for throughput and not power efficiency. This paper discusses the behaviour of the current task management subsystem (scheduler and loadbalancer) on a multi-core SMP system and its effectiveness in saving energy consumption under several situations (idle, moderate load). It then describes several techniques such as timer migration, task wakeup biasing and related heuristics for reducing energy consumption. The paper also looks at possible methods to mitigate interrupts for energy savings during different workloads and concludes by discussing some results of these new strategies.
Corrosion resistance potential of boron phosphide films in a naval environment

The anode characteristic differences of n- and p- type germanium in aqueous solutions has been investigated in the early 1950's. n-type electrodes were always pitted after being made anode above the breakdown potential, whereas p-type electrodes exhibited an electro-polished surface finish. Diamond Like Carbon (DLC) coated germanium has been used extensively as the material of choice in harsh sub-surface and surface seawater environments. It has been widely demonstrated that DLC coated germanium provides limited protection and that electrolytic etching of the germanium still occurs. This paper investigates the corrosion resistance properties of Boron Phosphide on germanium in a naval environment by presenting measured, comparative data from tests and field trials.
Impact of Megasonic Activation with Different Chemistries on Silicon Surface in Single Wafer Tool

More and more, 300mm manufacturing promotes a single wafer tool approach in FEOL cleaning. Previously, we reported an advanced surface preparation process based on dilute HF/HCl/DIW and O3/HCl/DIW chemistries coupled with megasonic activation during the ozone step only, on a 300mm single-wafer platform [1]. As throughput consideration implies shorter process time, the activation of megasons during the whole cleaning step could be of interest for very small particle removal efficiency. Nevertheless, extending megasonic activation to the entire process sequence leads to degraded results on silicon surface. Indeed, damages are created at 90 and 65nm defect inspection levels when megasonic activation is used in the presence of both HF species and on hydrophobic silicon surface. In this paper, we demonstrate that the megasonic activation (Megs) generates randomly and locally oxidized species which may be the main cause of damages in the presence of HF chemistry. Additional characterizations are performed to understand this problem (haze inspections, ATR analysis and contact angle measurements).
Designing for (un)serendipity - computing and chance

The tale of a lame, one-eyed, toothless camel may not, at first glance, seem an auspicious start for ground-breaking discoveries of penicillin, X-rays and chocolate chip cookies. However, when Horace Walpole coined the word serendipity in 1754, based on the tale of ‘The Three Princes of Serendip’ and the aforementioned camel, he was giving name to the accidental sagacity (i.e. accidental wisdom) involved in many scientific discoveries and inventions, where there is “no discovery of a thing you are looking for”.
Subclinical cardiovascular changes in pediatric solid organ transplant recipients

It is already a commonplace conclusion drawn from many adult and pediatric registries and clinical studies that patients with end-stage renal disease (ESRD) are at high risk of cardiovascular disease (CVD). Renal transplantation (RTX) decreases that risk; however, it still remains much higher than that of the general population (1–3). Following transplantation, there are numerous early events and complications that influence outcome, including graft and patient survival (4). In the case of kidney transplantation, early bacterial and viral infections, acute rejection, delayed graft function, and some surgical technical issues are salient and serious complications requiring particular attention and care. In the case of other solid organ transplants, these initial events may be complicated by the occurrence of acute kidney injury (5, 6). This critical early post-transplant phase is generally followed by a “honeymoon” period, with stable graft function and improving quality of life. This may falsely reassure the medical team and patient and family that all is well and may limit attention to meticulous monitoring and control of graft function, blood pressure, and therapeutic drug monitoring.