Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanocarriers as Magic Bullets in the Treatment of Leukemia

Leukemia is a type of hematopoietic stem/progenitor cell malignancy characterized by the accumulation of immature cells in the blood and bone marrow. Treatment strategies mainly rely on the administration of chemotherapeutic agents, which, unfortunately, are known for their high toxicity and side effects. The concept of targeted therapy as magic bullet was introduced by Paul Erlich about 100 years ago, to inspire new therapies able to tackle the disadvantages of chemotherapeutic agents. Currently, nanoparticles are considered viable options in the treatment of different types of cancer, including leukemia. The main advantages associated with the use of these nanocarriers summarized as follows: i) they may be designed to target leukemic cells selectively; ii) they invariably enhance bioavailability and blood circulation half-life; iii) their mode of action is expected to reduce side effects. FDA approval of many nanocarriers for treatment of relapsed or refractory leukemia and the desired results extend their application in clinics. In the present review, different types of nanocarriers, their capability in targeting leukemic cells, and the latest preclinical and clinical data are discussed.
UNDERDETERMINED BLIND SOURCE SEPARATION*

This paper proposes a Gaussian mixture model-based Bayesian analysis for blind source separation of an underdetermined model that has more sources than sensors. The proposed algorithm follows a hierarchical learning procedure and alternative estimations for sources and the mixing matrix. The independent sources are estimated from their posterior means, and the mixing matrix is estimated by the maximum likelihood method. Because each source is conditionally correlated with others in its Markov blanket, the correlations between them are approximated by using linear response theory; this is based on the factorized approximation to the sources’ true posteriors. In this framework, each source is modeled as a mixture of Gaussians to fit its actual distribution. Given enough Gaussians, the mixture model can learn any distribution. The algorithm provides a good identification of the mixing system, and its flexibility speeds up the convergence. The iterative learning for Gaussians leads to a parametric density estimation for all hidden sources as well as their recovery in the end. The major advantages of this algorithm are its flexibility and its fast convergence. Simulations using synthetic data validate the effectiveness of the algorithm.
The Effect of Hypertension and Control of Hypertension on Health Related Quality of Life in Hypertensive Patients Attending Consultation Clinic for Internist Diseases at Al-Kindy Teaching Hospital

Worldwide, raised blood pressure is estimated to cause 7.5 million deaths, about 12.8% of the total of all deaths. This accounts for 57 million disability adjusted life years (DALYS) or 3.7% of total DALYS. Raised blood pressure is a major risk factor for coronary heart disease and ischemic as well as hemorrhagic stroke. Blood pressure levels have been shown to be positively and continuously related to the risk for stroke and coronary heart disease. In some age groups, the risk of cardiovascular disease doubles for each increment of 20/10 mmHg of blood pressure, starting as low as 115/75 mmHg [1]. If left uncontrolled, hypertension causes stroke, myocardial infarction, cardiac failure, dementia, renal failure and blindness, causing human suffering and imposing severe financial and service burdens on health systems [2,3]. In different studies conducted to assess the relation between QOL and hypertension, most of the studies reported lower scores in most dimensions as physical capacity, social functioning, mental health, psychological functioning, and vitality as compared to general population [4,5]. Hypertension markedly impairs quality of life in terms of both physical and mental health [6]. Carvalho and others pointed out that most of the time hypertension is clinically silent disease but still it impairs QOL [7].
Supplement to ``On High-dimensional Sign Tests"

where En` still denotes conditional expectation with respect to Fn`. Clearly, we have that I (n) N ,p,q = ∑n `=1D I n`, where D I n` is almost surely bounded, hence has a finite-variance. The asymptotic normality result in Theorem M-2.4 will then follow from Theorem M-B.1 provided that we establish the following two lemmas (in the proofs, we use the same notational shortcuts as in those of Lemmas M-B.1 to M-B.4).
Norwegian Institute for Water Research

The PIAC-project has been a multidisciplinary survey on acid rain in China. One goal has been to document effects of airborne acidifying compounds on vegetation, soil, soiland surfacewater and aquatic biota. Other goals have been to exchange knowledge between Chinese and Norwegian scientists, as well as visiting research sites in highly polluted areas in China and evaluating their need of support in a future collaborative monitoring and research program. Besides doing field measurements, we have collected samples at more than 20 sites in three areas in China, i.e. Chongqing, Guiyang and Guangzhou. Data from this survey may also be used in the RAINS-Asia model work, where more data are needed to validate and improve this model. Our survey documents negative effects of air pollution on all ecosystem levels investigated. The air concentration of sulfur in the urban and nearby areas is very high. The concentration of volatile organic compounds is generally high, which means that increased NOx emissions in coming years may create increasing O3 problems. Reduced photosynthetic activity in some plants is documented, as well as soil and surface water acidification. Aquatic biota also reflects the acidification status of the surface waters investigated. However, the degree of damage in these regions is difficult to assess, since too few sites are incorporated in the survey. Surface water acidification is currently not a major environmental problem in China and will presumably not become one during the next decades. This report also contains a status report about acidification in China (in Appendix A) as well as a proposed framework for a monitoring program based on Norwegian experiences (in Appendix D). 4 keywords, Norwegian 4 keywords, English 1. Luft forurensning 1. Air pollution 2. Forsuring 2. Acidification 3. Økosystem 3. Ecosystems 4. Kina 4. China Espen Lydersen (NIVA) ISBN 82-577-3287-7 Bjørn Olav Rosseland Project co-ordinator Head of Research Department Planning of an Integrated Acidification Study and Survey on Acid Rain Impacts in China
Temperature-Dependent Mechanical Properties of Graphene/Cu Nanocomposites with In-Plane Negative Poisson's Ratios

Negative Poisson's ratio (NPR), also known as “auxetic”, is a highly desired property in a wide range of future industry applications. By employing molecular dynamics (MD) simulation, metal matrix nanocomposites reinforced by graphene sheets are studied in this paper. In the simulation, single crystal copper with crystal orientation [1 1 0] is selected as the matrix and an embedded-atom method (EAM) potential is used to describe the interaction of copper atoms. An aligned graphene sheet is selected as reinforcement, and a hybrid potential, namely, the Erhart-Albe potential, is used for the interaction between a pair of carbon atoms. The interaction between the carbon atom and copper atom is approximated by the Lennard-Jones (L-J) potential. The simulation results showed that both graphene and copper matrix possess in-plane NPRs. The temperature-dependent mechanical properties of graphene/copper nanocomposites with in-plane NPRs are obtained for the first time.
Analysis on resident's spectrum of disease and death in cadmium-polluted area

Objective To investigate the effect of cadmium(Cd) pollution on disease and death of the residents.Methods ix physical villages of the cadmium polluted area were carried out the retrospective investigation on the fiver year death.Results The infant mortality rate and the premature delivery rate in the Cd polluted area were higher than those of unpolluted areas.The specturm of disease and death of the polluted area was significantly different from the unpolluted area of the same county and from the mountain districts of the Fujian province,The standardized mortality rate of malignant tumour,respiratory system diseases,digestive system disease and the neonatal diseases were higher than those of the unpolluted area.Conclusion The residents in the polluted area were influenced by the Cd pollution.
Establishment of rabbit model bearing VX2 liver tumor experimentation and discussion of the selective hepatic arterial catheterization

Objective To introduce an animal model of implanted VX2 liver tumor in rabbits with discussing the selective arterial catheterization during TACE. Methods VX2 carcinoma cells were grafted into the left and right lobes of liver in 80 New Zealand white rabbits.2-3 weeks later,51 rabbits were performed with fine needle direct liver arterial catheterization followed by DSA and embolization.10 others were performed with percutaneous trans-femoral retrograde approach of hepatic arterial catheterization and another 10 with retrograde gastroduodenal arterial catheterization. Results Seventy one rabbits(98%) were grafted with VX2 tumor cell successfully.The rates of successful catheterization and superselective arterial embolization with direct fine needle puncture were 98% and 88%,respectively,while the successful rates of other two methods were only 30% and 40%. Conclusions Grafted VX2 liver tumor rabbit model is suitable for interventional experimentation.Fine needle direct liver puncture is a good technique for superselective embolization during animal experiment.
Survey of Stochastic Computing for Hardware implementation

Stochastic Computing (SC) is another substitute way to deal with digital information. With ongoing advances in Internet of Thigs (IOT) and wearable gadgets it is interesting to implement Artificial Neural Network (ANN), Image Processing applications on reconfigurable platform. However, several elements and very complicated connections are usually required, which leads to more hardware and power consumption. Stochastic Computing (SC) meet stringent requirement in embedded and mobile IOT devices. SC is an alternate approach to deterministic computing that treats binary data as probabilities. SC employs very low-complexity arithmetic units. SC is popular in immensely parallel systems and is exceptionally tolerant to soft errors. SC based hardware execution achieves low hardware foot print, low power and energy competent circuits while preserving high accuracy. This paper surveys SC's the low cost, low complexity, error tolerant, alternative to binary computing
Contextualized Relevance Feedback for Precision Medicine

Precision Medicine (PM) is viewed as an information retrieval (IR) task, in which biomedical articles containing treatment information about specific diseases or genetic variants are retrieved in response to patient record, aiming at providing medical evidence to the point-of-care. Previous PM approaches are mostly based on unigram matching of individual query terms, or concepts, to the target articles to produce the ranking list, while ignoring the context of the matched query terms of concepts. To this end, this paper presents a preliminary investigation of utilizing contextualized representation of text for pseudo relevance feedback (PRF) to enhance PM search effectiveness. By considering the multi-aspect word relations, we propose a $BERT_{NPRF}$ model to integrate PRF with the fine-tuned BERT model for contextualized interaction of document-document pairs. Experimental results on the standard Text REtrieval Conference (TREC) PM track benchmark show that our proposed method with interpolation can improve the performance in PM.
Design of an Indoor Localization System based on WLAN for Assisting Victim’s Evacuation Process

Disaster can cause damage to the buildings and can make the victims trapped inside the buildings. During this time, the rescuer team will try to evacuate the victims despite the difficulties in finding out the exact number of victims and the location of victims. This research is carried out to solve that problem by implementing an indoor localization system. Indoor localization system aims to find out person or object location using frequency emitted by wireless devices. This research will use WLAN-based indoor localization technology to design a smartphone application that can be used during a victim’s evacuation process from inside of a building. Positioning using WLAN technology or Wi-Fi can utilize Receive Signal Strength (RSS) to get the victim’s position. The victim’s estimated position will be calculated by using Euclidean distance to find the coordinates of every points in a building and the coordinate of victim. The victim’s coordinate will be stored in database server so that the data will be available and can still be accessed by the rescue team even though the building has been damaged. The design of the indoor localization system will be implemented as an Android application that is still under development.
A Fast and Simple Method for Obtaining Microcircuit Card Information

The traditional microcircuit card generally adopts the Crypto-1 private encryption algorithm, and its main components are a pseudo random number generator (PRNG), a 48-bit linear feedback shift register (LFSR) and a nonlinear function. This paper mainly starts off from the perspective of the design flaw of the Filter Function algorithm: first, the characteristics of the random sequence are generated when the card reader swipes the card, and the same sequence is generated when the microcircuit card is re-established after each power failure; then, by controlling the time and the position of the microcircuit card, a random sequence of the moment after the microcircuit card acquires the energy is obtained, thereby implementing data modification; finally, the paper verifies by experimental methods, and the results show that the information of the microcircuit card can be indeed obtained.
Dynamic A-MPDU adaptation method for airtime fairness in channel bonding-ready WLANs

Channel bonding is a technology to increase the transmission rate by bundling and using multiple continuous channels. However, the communication performance is likely to degrade frequently due to the channel competition caused by the rapid increase of the wireless LAN devices. Dynamic channel bonding is expected to become the mainstream in the future from the viewpoint of efficient channel utilization even under the severe competitive condition. However, since the implementation of the dynamic channel bonding to real PC and simulator is in the preliminary stage, the detailed performance investigation has not been carried out. None of existing studies examines the performance of the dynamic channel bonding at the frame level with CSMA/CA functions under the diverse channel competition condition. In this study, we first examine the performance of the dynamic channel bonding with CSMA/CA functions through theoretical approach (2 M/M/1/K) from the view point of frame level. In addition, we then implement the channel bonding mechanism into the Scenargie simulator and then verify its effectiveness through the comparison between simulation results and theoretical ones. Simulation results show that the dynamic channel bonding is suffering from the performance degradation due to the performance anomaly problem caused by the airtime unfairness, we thus propose a dynamic A-MPDU adaptation method. We showed that our proposed method can maximize throughput while achieving airtime fairness, irrespective of different patterns of channel competition.
Accelerating the Analytical Modeling of Memory Level Parallelism by the Probability Analysis

Memory level parallelism (MLP), which refers to the number of memory requests concurrently held by Miss Status Handling Registers (MSHRs), is an indispensable factor to estimate cache performance. Unfortunately, due to the complexity of obtaining the maximum number of memory instructions or cache misses among all dependence paths, previous works in MLP modeling are very time-consuming in trace profiling. In this paper, we propose a fast model for evaluating MLP without analyzing all dependence paths in the instruction windows. Instead, we construct a probability model to estimate the maximum number of cache misses among all dependence paths in the instruction windows fed with some easily obtained inputs. By doing so, we greatly reduce the time overhead of the MLP model with a slight drop in accuracy. Twelve benchmarks chosen from Spec2006 are adopted for evaluating the accuracy and time overhead of our model. The average error of our model compared with the results of Gem5 simulations is around 9%, while the time overhead of the MLP evaluation process can be decreased to about half of previous models.
Punch-through and DIBL Effects Exposing Nano-node SOI FinFETs under Heat Stress

Through the electrical measurement plus the heat stress to enhance the existed or latent defects of FinFETs in the nano-node process flow is a useful metrology. This method not only effectively and timely provides the mapping analysis in a whole wafer, but the sensed data may be correlated to the process variation and optimization in statistical analysis. Besides the common electrical characteristics in ON/OFF current, the punch-through and drain-induced barrier lowering (DIBL) effects like a pair of detectors are good tools to probe the channel integrity. More process parameters of VT implantation related to these two effects are discussed.
Stereo Visual Odometry with Light and Adaptive Feature Tracking

Localization technology plays a key role in autonomous driving. Stereo visual odometry is a meaningful visual localization method to estimate the pose of autonomous vehicles. VINS-Fusion provides a state-of-the-art stereo visual odometry with Kanade-Lucas-Tomasi (KLT) tracker to achieve fast feature tracking. However, KLT tracker is prone to fall into local minima in urban environments due to illumination changes and large displacements, leading to catastrophic cumulative drift over time. Aiming to solve this problem, we present a light and adaptive feature tracking technique for VINS-Fusion to get a reliable set of measurements for pose estimation. First, a disparity constraint is incorporated into left-right check to refine the measurements. Next, we propose a light bi-circular check to further remove outliers, which has high efficiency with the ingenious design. Additionally, an adaptive strategy for feature selection is proposed to dynamically balance the quantity and quality of the measurements. Experiments demonstrate that our method outperforms VINS-Fusion by producing more accurate pose estimation with 20% speedup on the KITTI odometry benchmark.
Design and Implementation of Model Autonomous Sentry Gun Using Image Processing and Motion Tracking

Development of Auto Tracking Technology and Image Processing is very broad. One of them in the field that utilizes Autonomous Tracking technology is the military field. Autonomous Tracking technology is used by weaponry machines so that it becomes more accurate and efficient when compared to humans. Autonomous Sentry Gun is a tool that can shoot automatically by knowing the coordinates of the target. In the research entitled Design of Sentry Gun Model using Image Processing and Motion Tracking, tracking tests were carried out on the target given different colors and the target area varied by distance for each test. In the first test RGB color tracking was carried out with the target area varied and the result was the color that had the farthest distance was red with a distance of 223 cm with an area of 54 cm2. In the second test of RGB color tracking with the same area, the color results obtained with the farthest tracking distance is yellow with a distance of 430 cm with an area of 415 cm2. Meanwhile, the minimum tracking distance was found at purple which is 340 cm with an area of 415 cm2. The results of the experiments showed that Sentry Gun was working in accordance with the specified specifications which can distinguish the target color so that the tracking distance of each color was different.
Skin Cancer Detection using Cellular Resolution Optical Coherence Tomography

The detection of skin cancers has been studied using the full-field optical coherence tomography. High-speed CMOS camera with high brightness light source were employed to achieve real-time imaging with cellular resolution for the detection of cellular atypia and structural derangement. Animal model on squamous cell carcinoma shows greater than 90% accuracy.
Is Seeing Believing? Video Forgery through Object-based Editing Techniques

Videos are generally considered to provide stronger forensic evidences than still images. This is why surveillance video is often used in investigations and information-gathering as an important and credible piece of evidence. It is evident that the ever-increasing capabilities of digital video processing have made surveillance video easy to operate and can even change images to one’s liking. Although video editing software (such as Adobe Premiere) can be used to easily tamper with digital video without leaving visible clues, it requires proficient editing techniques and processing time. This study focuses on object-based video editing technology. It shows how this object-based video editing technology could adjust the spatial domain properties of objects in the video, such as deletion, displacement, and copying. It is also possible to adjust the object in the time domain so that the temporal relationship between objects changes or even reverses. These features show the potential problems of video as evidence. On the other hand, the same technology can be applied positively to eliminate unwanted objects in the video to make the video smoother, clearer and more accurate.
Cross Connected Source based Reduced Switch Count Multilevel Inverter Topology with Fault Tolerance

In this paper, topology of a Cross Connected Source based Reduced Switch Count (CCS-RSC) Multilevel Inverter (MLI) has been analyzed with fault tolerance for a 7-level fed ‘R’ load. The proposed CCS-RSC MLI generates higher voltage levels with optimum number of power switches. The configuration results in an improved power quality by due to reduction in the harmonic content, compared to traditional Multilevel Inverters (MLIs). The CCS-RSC MLI requires only ‘m+1’ power switches for ‘m’ levels, whereas the traditional MLIs require ‘(2m-1)’ switches. Therefore, CCS-RSC inverter requires only eight power switches and three DC sources to generate 7-levels in the output voltage. The redundant switch combinations get limited due to the decrease in power switches. Consequently, the possibility of fault tolerant capability gets effected for a few particular faulty switches. The proposed inverter is analyzed by reconfiguring the switching tables for fault tolerant procedure for an open circuited single switch. Also, the proposed inverter with sine wave reference and inverted sine carrier modulation strategy has a lower %Voltage THD compared to traditional MLI. The effective performance of the suggested topology for a 7-level single-phase CCS-RSC inverter with fault tolerance is validated with MATLAB/SIMULINK for open circuit fault on each of the power switches.