Miracle-dz/UniFAR-FTUs huggingface dataset:
Sway: Traffic-Aware QoS Routing in Software-Defined IoT

In this paper, we propose a traffic-aware quality-of-service (QoS) routing scheme in software-defined internet of things (SDIoT) network. The proposed scheme exploits the unique features of software-defined networking (SDN), such as flow-based nature, and network flexibility, in order to fulfill QoS requirements of each flow in the network. We consider two types of QoS routing strategies—delay-sensitive and loss-sensitive—for incoming packets from end-devices in the network. The former is devised to deal with delay-sensitive flows, and the latter deals with loss-sensitive flows, in order to maximize the overall network performance. We propose a greedy approach based on Yen's K-shortest paths algorithm to compute the optimal forwarding path, while considering the QoS requirements of each packet. Consequently, the SDN controller deploys adequate flow-rules at the forwarding devices in the network. Extensive simulation results show that the proposed scheme significantly reduces the end-to-end delay and the percentage of flows which violate QoS constraints compared to the benchmarks considered in the study. It is also observed that the proposed scheme adequately satisfies the QoS requirements for both type of flows in contrast to the existing schemes. In particular, with 2000 flows in the network, the proposed scheme achieves 13%, 14% and 15% (with AttMpls topology) and 38%, 37% and 39% (with Goodnet topology) reduction in QoS violated flows as compared to the existing LARAC, SPD, and MRC schemes, respectively.
0 “ Other People ’ s Money ” : Mum and Dad Investors vs the Professionals *

We utilize seventeen years of comprehensive daily portfolio and trading data identified at the level of every Mum and Dad investor to analyze the relative trading performance of the population of Finnish households making their own decisions, all domestic financial institutions, and the global population of foreign delegated institutions investing other people’s money. We utilize a new methodology we dub the “holding-period-invariant” (HPI) portfolio approach. The conventional calendar-time portfolio approach imposes a heroic assumption that all investors mechanically realize (i.e., trade) their portfolio at specified intervals corresponding to an assumed horizon. By contrast, our methodology is free of such bias and allows for the endogenous nature of investment timing decisions made by numerous informed households. Adopting a random informationless trading benchmark, we find that the households who choose to trade for themselves are economically and statistically superior traders, achieving an impressive internal rate of return of 42.84% p.a. , or 0.0288% of traded value, with foreign institutions, is consistent with the predictions of Hayek (1945). Our finding is contrary to some of the existing empirical literature on Mum and Dad investors derived from calendar-time portfolios. We also show that utility maximizing household and domestic institutional trading can be explained by their receipt of a daily private signal of fundamental value derived from the entire past history of informed trades and prices, statistically rejecting the nested noisy partially revealing rational expectations equilibrium hypothesis.
Fast Unsupervised Object Localization

As opposed to image classification, object localization is a computer vision problem whose solutions have not measured up to human level performance, even with the use of deep learning. Common approaches to address this problem in the deep learning framework, are moving sliding windows across the image, training neural architectures to predict bounding boxes, and using classic image processing techniques such as SIFT and Region Proposals. None of these methods utilize the innards of the classification neural network to localize images. In fact, one could argue that these methods are created with the assumption that neural networks are just abstruse black boxes that give us an output for every input. We posit that a neural network for classification has enough usable spatial information to localize objects. We introduce a powerful and novel technique that harnesses only a pretrained CNN to localize an object in an image. To be clear, we do not train on any bounding box data. We obtained very promising results. In our validation we found the center of the localization method’s bounding box was within the ground truth bounding box in more than 90% of the cases. The core idea of our technique can be extended to other computer vision problems such as multi-class object localization and image segmentation. In addition, since our technique works so well with only a classification neural network, there is good reason to believe that we can improve the methods that currently train on bounding box data.
THE ACIDOPHILIC BACTERIA ABILITY TO PRODUCE METALLOENZYMES RESPONSIBLE FOR THE STARCH DEGRADATION IN THE PRESENCE OF HEAVY METAL IONS CISMA

An action of removing heavy metal ions from aqueous solutions consists in their biosorption using the acidophilic heterotrophic bacteria of the Acidiphilium genus present in aquatics and ground environments. The assimilative capacity of heavy metals by the aerobe bacterial biomass has been investigated and compared to different types of biomass, grown in laboratory conditions by exploiting synthetic wastewater. Some of these types of biomass have a high potential for biosorption, appreciated as competitive in the biotechnological detoxification of industrial effluents. Efficiency of the extracellular enzymatic activity of the acidophilic heterotrophic bacteria is correlated in direct proportion to the amount of organic substances from the environment, the concentration of oxygen and heavy metallic ions. In this context, this paper presents the influence of Cu, Zn and Ni on the enzymatic activity of the extracellular starch degradation in the presence of acidophilic heterotrophic bacterial populations of the Acidiphilium genus in order to increase the efficiency of organic substances deterioration ability for contaminated environments with heavy metal ions. The obtained results showed a stimulation of starch degradation by the action of extracellular amylolitic enzymes synthesized by acidophilic bacterial populations in the presence of heavy metal ions. In addition, the performed studies allowed the selection of bacterial cultures with increased degradation capacity of organic substances under extreme environmental conditions for removal of heavy metallic ions from industrial waste waters.
The Small Number System

I argue that the human mind includes an innate domain-specific system for representing precise small numerical quantities. This theory contrasts with object-tracking theories and with domain-general theories that only make use of mental models. I argue that there is a good amount of evidence for innate representations of small numerical quantities and that such a domain-specific system has explanatory advantages when infants’ poor working memory is taken into account. I also show that the mental models approach requires previously unnoticed domain-specific structure and consequently that there is no domain-general alternative to an innate domain-specific small number system.
WELL-FORMEDNESS , CONSISTENCY AND COMPLETENESS OF GRAPHIC MODELS

This paper clarifies the notions of well-formedness, consistency and completeness of graphic models. A model or a diagram is well-formed if its structure satisfies the syntactic rules, especially its elements are type compatible if a type system is defined. When models are considered as specifications of software systems, consistency means that there exists a system that satisfies the specification. Completeness means that all the systems that satisfy the specification are what users want. The paper proposes a framework for the formal definition of the abstract syntax and type systems of modelling languages. A formal notation is advanced by extending and adapting BNF. A first order language for the definition of consistency and completeness constraints are also presented and illustrated by examples.
A Perfect Tracker on CVPR TB-50 & ALOV 300 + +

Visual object tracking is one of the fundamental problems of computer vision, with wide-ranging applications including video surveillance, human-machine interfaces and robot perception. Although visual tracking has been investigated intensively in the past decade, it is still an enormous challenge in real application because of various factors such as pose, occlusion, scale and illumination. Recent tracking algorithms can be split into two main modules generally: feature extraction and tracking model. This report shows a perfect online tracker, which was extensively evaluated on the CVPR 2013 Tracking Benchmark (TB-50) including 50 sequences and the Amsterdam Library of Ordinary Videos (ALOV300++) dataset. The experimental results demonstrated the superior performance of it in comparison with other state-of-art trackers.
A novel technique for Reversible Information Hiding

The data in transit on the Internet is quite vulnerable to the various attacks. Mostly, an encrypted data is sent to avoid unauthorized interrupt. Digital watermarking allows information to be hidden and embedded in multimedia data like text, images, audio, video etc. Whereas reversible watermarking schemes are considered lossless as extracting the watermark does not affect the original image and it can be restored completely. We can classify the watermarking techniques according to various criteria like domain of the data, its visibility to the attackers, robustness and also according to the technique used for the retrieval at the receiver end. In this paper, we will consider approaches from different domain, like spatial or transform, for hiding information in some cover image. This paper proposes a novel reversible data hiding approach that can extract the hidden information from original image without any loss of the information. We will also discuss about lossy and lossless image format, where stressing on 8-bit and 24-bit, . bmp and . jpeg images. The hidden message will be converted in message digest that is secure hash code using MD5. This code will be stored in a digital image in such a way that it is not human perceptible.
L O ] 2 J ul 2 01 9 Core First Unit Propagation

Unit propagation (which is called also Boolean Constraint Propagation) has been an important component of every modern CDCL SAT solver since the CDCL solver was developed. In general, unit propagation is implemented by scanning sequentially every clause over a linear watch-list. This paper presents a new unit propagation technique called core first unit propagation. The main idea is to prefer core clauses over non-core ones during unit propagation, trying to generate a shorter learnt clause. Here, the core clause is defined as one with literal block distance less than or equal to 7. Empirical results show that core first unit propagation improves the performance of the winner of the SAT Competition 2018, MapleLCMDistChronoBT.
Potential Impacts of Liquid-Metal Plasma-Facing Components on Heating and Current Drive Actuators for a Fusion Nuclear Science Facility

Abstract This paper addresses the potential impact of liquid metal (LM) plasma-facing components (PFCs) for the heating and current drive (H&CD) actuators on the Fusion Nuclear Science Facility (FNSF) fusion reactor. Fulfilling the high neutron fluence mission of the FSNF requires steady-state operation for extremely long pulses (months to years) between maintenance opportunities. The use of LM as a surface material is one strategy for extending the lifetime of the PFCs for long pulse operation in a high heat flux, high neutron flux environment like that of the FNSF. Liquid metal PFCs provide possible pathways forward on many difficult aspects of a fusion reactor; however, the LM PFCs also bring new challenges and unknowns with respect to the H&CD actuators needed to provide steady-state operation. The development of LM-compatible materials for radio-frequency (RF) antennas will be critical, as well as strategies for minimizing contamination of antenna surfaces and the core plasma. Successful deployment of LM PFCs on the FNSF will require operational experience with RF in a LM environment both on test stands and in an integrated toroidal environment.
High Resolution Radiation Hardened DAC in CMOS-SOI Featuring a Return-to-Zero Matrix

We present a current-steering, low-noise, radiation hardened Digital-to-Analogue converter, optimized to operate in the frequency range between DC and 50kHz. The DAC receives 24-bit sampled data in a synchronous serial format and converts it into a differential current analog signal. It uses a third-order multi-bit Sigma-Delta modulator, which provides superior noise and linearity performance. The embedded interpolator follows a multiple-stage architecture and consists of an FIR equiripple low-pass filter followed by two cascaded stages of Half-band equiripple filters. The last stage is a programmable SINC filter, which provides variable interpolation ratios allowing sampling rates as high as 310kHz. The system operates on a single clock domain, which is provided externally. The output current matrix features a Return-to-Zero (RTZ) technique to improve the linearity by ensuring that each elementary current source is zeroed, regardless the data value of the sample sequence. The DAC is implemented in a rad-hard 150nm CMOS-SOI process, exhibits an SNR figure of better than 108dB, and consumes 62mW of power.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

With the rapid development of the Internet and the proliferation of the number of its users, the Internet is becoming an ideal environment for the criminal activities such as online scams and child sexual abuse [1.10]. Usually, it is difficult to trace the culprits since they will not use their real identity on the Internet, yet by examining the evidence left by the culprits such as scam emails or abusive messages, with the support of the authorship analysis research, it can help to reveal more information about the original writers of those messages by analyzing the writing style, increasing the probability of finding the criminals. This thesis is divided into two parts. In the first part, we will search for the methods and techniques that are being used in the authorship identification research area and then implementing them into a workable prototype. Then the implemented prototype will be examined and evaluated for the qualitative (the accuracy level in identifying the correct original writers of the given texts), and quantitative (the prototype’s execution time) attributes. In the later part of this thesis, four different improvements for the existing methods and techniques will be introduced and tested for their performance. The performed experiments show that in the authorship identification task, the support vector machine classifier can archive a better result from 10% to 30% compares to the other types of classifier in the qualitative experiment. Furthermore, the authorship identification task is not just a supervised learning problem; the results from four different improvements showed that the unsupervised learning technique can also help to improve the performance of the existing methods and techniques. In general, the accuracy level of the prototype, after applying the proposed improvements is improved by 05% to 10% while the performance is improved by 20% to 50%.
Effects of various feeding and starvation strategies on growth, hematological and biochemical parameters, and body composition of Caspian brown trout (Salmo caspius Kessler 1877) parr

This study was carried out to investigate the effects of starvation and feeding regimes on growth performance, haematological and biochemical parameters of blood and body composition of Caspian brown trout parr. For this purpose, 900 fish (average weight: 12.5±1 g) were stocked in 300-l tanks (18 tanks at a stocking rate of 50 fish in each tank) using an open system. Six experimental groups composed of feeding and starvation regimes were considered for the experiment as follows: FFF (Six weeks feeding), SSS (Six weeks starvation), SFS (Two weeks starvation + two weeks feeding + two weeks starvation), FSF (Two weeks feeding + two weeks starvation + two weeks feeding), FS (Three weeks feeding+three weeks starvation), and SF (Three weeks starvation + three weeks feeding). According to results obtained, the growth rate (GR), special growth rate (SGR), condition factor (K) and hepatosomatic index (HSI) decreased as the length of starvation periods increased (p 0.05) while the highest values of red blood cells (RBCs) and white blood cells (WBCs) were observed in the SSS group (p 0.05). In conclusion, our results showed that starvation has significant physiological and morphological effects on Caspian brown trout parr.
Predicting Re-loan Success based on Friendship Network Characteristics in the Online Microloan Marketplace Completed Research

Online micro-loan marketplaces cannot accurately and effectively approve loan applications due to the uncertain opportunistic behavior of loan applicants and the possibility of loan defaults by loan applicants. To address this challenge, in this study we integrate signaling theory, the social structure of competition, and the concept of homophily to develop a research model to predict a loan applicant’s re-loaning success by examining his/her financial status, friendship network characteristics, and friendship network centrality. Data of 683 anonymous and distinct loan applicants at a major online micro-loan marketplace in China largely support our hypotheses, highlighting the three key signals of a successful re-loan approval, a loan applicant’s credit card default, the number and the percentage of his/her friends with reloan approvals in the focal micro-loan marketplace. Research and practical implications are discussed.
Orijinal Araştırma Evaluation of Regional Anesthesia Complications in Caesarean Section Sezeryan Operasyonlarında Rejyonel Anestezi Komplikasyonlarının Değerlendirilmesi

Aim: We aimed to evaluate the complications of regional anesthesia techniques in caesarean operations. Material and Methods: Patients who underwent caesarean operation managed with regional anesthesia between January 2010 and January 2011 were included in this study. Demographic data, regional anesthesia method, position during approach, number of attempts, patient feelings during local anesthetic injection, dermatomal level, and complications were recorded. The results were analyzed and presented for each regional anesthesia technique. Results: A total of 425 were performed in the study period. Totally 269 caesarean sections under regional anesthesia were included in this study. Caesarean sections were performed at a rate of 1.5 % in patients below 20 years of age, 91.1 % in 20-34 years of age and 7.4 % in over the age of 35 years. Specifically, spinal anesthesia, epidural anesthesia, and combined spinal-epidural anesthesia were applied to 236, 9, and 24 patients, respectively. Spinal anesthesia was the most frequently applied regional anesthesia technique in this study. The most common sensation during local anesthetic injection was feeling of warmth at a rate of 54.6 %. Post dural puncture headache was observed at a rate of 6.3 % (n=15), and backpain 8.8 % (n=21) in the spinal anesthesia group. Neurological complications occurred in 2 patients. Discussion: The present study revealed that the complication rates of regional anesthesia techniques in our university had consistent results with the current literatures.
Microscopy Study in Malaria by using PCR

Accurate identification of Plasmodium infections in community surveys is essential to successful malaria control. Microscopy and rapid diagnostic tests (RDTs) are the main techniques used to diagnose malaria in field-based surveys. While microscopy is still considered the gold standard, RDTs are growing in popularity as they allow for rapid and inexpensive diagnosis. Using data from a prevalence survey conducted in north-western Angola in 2010, the authors aimed to compare the performance of microscopy and RDTs in identifying Plasmodium falciparum infections, using polymerase chain reaction (PCR) as the gold standard.
Triptolide sensitizes cisplatin-resistant human epithelial ovarian cancer by inhibiting the phosphorylation of AKT

Advanced and chemotherapy-resistant ovarian cancer causes high mortality of ovarian cancer, and it is important to find safe and effective drugs to reduce the chemotherapeutic resistance of ovarian cancer. In our study, we attempted to clarify the resistance mechanisms of SKOV3/DDP cells in vitro and evaluated the sensitization to triptolide (TPL) in vivo. Our results indicated that the overexpression of AKT and p-AKT greatly enhanced the cisplatin (DDP) tolerance of SKOV3/DDP, and the combination of DDP+TPL had a significant tumour inhibition effect compared to DDP treatment (p<0.05), via reducing the expressions of p-PI3K, p-Akt, Survivin, VEGF and MMP-2, and the increase of Caspase-3. Collectively, these results suggest that the synergistic anticancer effect of TPL and DDP warrants their potential clinical applications in further.
Do rheumatoid arthritis patients have more major complications and length of stay after lower extremities fracture surgery?

Abstract Patients with rheumatoid arthritis (RA) have a high risk of cardiovascular diseases and fractures. This retrospective cohort study explored whether patients with RA face higher complication risks or longer hospital stays than other patients when they had a lower limb fracture that required the surgery. Patients aged >45 years who received lower limb fracture surgeries between 2005 and 2012 were selected from the National Health Insurance Research Database, and 10 related variables including sex and age were used in propensity score matching to pair RA patients with non-RA patients in a 1:4 ratio. The final study sample comprised 1109 patients with RA and 4436 non-RA patients. The results indicated that 5.57% of the study sample had postoperative complications, accounting for 5.05% of patients with RA and 5.70% of the control group. After conditional logistic regression analysis was performed, the risk of major complications has no significant differences between patients with RA and the control group (odds ratio [OR] = 0.87; 95% confidence interval [CI]: 0.61–1.24; P > .05). However, the comorbidity severity score exerted a significant effect on complications; patients with scores ≥3 were 2.78 times more likely to experience complications (OR = 2.78; 95% CI 1.52–5.07). When considering different types of complications, patients with RA were less likely to be exposed to the risk of stroke (OR = 0.48). After controlling all related factors, no significant differences were observed in the complication risks or deaths between the 2 groups (P > .05). Regarding hospitalization length, the average stay for all patients was 8.12 days; after controlling related factors, the hospitalization length for patients with RA was 0.97 times that of the control group, which was nonsignificant (P > .05). These results may provide some information to healthcare professionals when providing treatments.