Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine Learning Techniques for Breast Cancer Analysis: A Systematic Literature Review

Summary Breast cancer (BC) is one of the most common cancers and is known to be the leading cause of death among females around the world. Breast cancer occurs when cells in the breast develop a malignant tumor. Detecting BC at an early stage with state-of-the-art technologies helps in treating BC and reduces the risk of death. Currently, mammography is the most commonly used technique for detecting BC. In order to improve the mammogram analysis, researchers have studied the feasibility of using artificial intelligence to help doctors in detecting any changes that may lead to cancer. This review paper investigates utilizing machine learning (ML) algorithms for BC prediction and classification, which will be beneficial in early diagnosis and treatment for BC and for future researchers in exploring the different ML techniques and selecting the most suitable one for their future research.
Investigating The Mediating Role of Positive Affection On the Relationship Between Attachment Styles and Maladaptive Schemas of Depressed Women

: The objective of this study was to investigate the mediating role of positive affection on the relationship between attachment styles and maladaptive schemas of depressed women. The method of this research is descriptive-correlational. The statistical population of this study included all depressed women admitted to Sina Hospital in Mashhad in 2017. The sample of study was selected using convenient random sampling method. To collect data, the Adult Attachment Styles Questionnaire (AAI), the Short Form of the Young's Early Maladaptive Schema Questionnaire (1988), Watson & Clark Positive Affection Questionnaire (1988), and Beck Depression Scale were used . The results of analysis of ANOVA showed that attachment styles and early maladaptive schemas directly and indirectly have significant effect on depression. The results of this study also showed that positive affection plays mediating role in the relationship between attachment styles and early maladaptive schemas and depression. In other words, attachment styles and early maladaptive schemas with leaving impact on positive affection of individuals decrease depression, and the therapists and counselors in counseling and mental health centers can take necessary medical measures to treat the depression by examining type of attachment style and early maladaptive schemas of people.
Phase Transitions in a Bose-Hubbard Model with Cavity-Mediated Global-Range Interactions

We study a system with competing short- and global-range interactions in the framework of the Bose-Hubbard model. Using a mean-field approximation we obtain the phase diagram of the system and observe four different phases: a superfluid, a supersolid, a Mott insulator and a charge density wave, where the transitions between the various phases can be either of first or second order. We qualitatively support these results using Monte-Carlo simulations. An analysis of the low-energy excitations shows that the second-order phase transition from the charge density wave to the supersolid is associated with the softening of particle- and hole-like excitations which give rise to a gapless mode and an amplitude Higgs mode in the supersolid phase. This amplitude Higgs mode is further transformed into a roton mode which softens at the supersolid to superfluid phase transition.
Spatio-temporal variations in conservative and non-conservative properties of the surface seawater along the Red Sea coast, Egypt

This study investigated the Spatio-temporal variations in the physicochemical properties of the surface seawater along the northern Red sea. 41 seawater samples were gathered from Ras Gharieb, Hurghada, Safaga, and Qusier cities to measure conservative (temperature, DO, salinity, pH) parameters. In parallel, non-conservative parameters (ammonia, phosphorous, nitrite, nitrate) were analyzed via a colorimetric-spectrophotometer instrument. Our findings revealed that physical parameters fluctuated between 19.01 ± 0.75 - 35.01 ± 0.47 ºC, 5.05 ± 0.54 - 11.70 ± 1.06 mg/l, 39.81 ± 0.35 - 42.31 ± 0.50 ‰, and 8.10 ± 0.14 - 8.50 ± 0.44 for temperature, DO, salinity, and pH, respectively. While chemical parameters ranged from 0.12 ± 0.06 to 1.53 ± 0.20 mg/l for ammonia, BDL to 1.71 ± 0.23 mg/l for phosphorous, BDL to 1.38 ± 0.05 mg/l for nitrite, and 0.09 ± 0.06 to 4.50 ± 1.22 mg/l for nitrate. Statistically, no discernible variation was detected among different seasons for all measurements except temperature, DO, and phosphorous ( P < 0.05). In addition, Pearson’s correlation analysis showed some positive or negative relationships between temperature and salinity (r = 0.75), salinity and pH (r = 0.50), temperature and phosphate (r = 0.70), salinity and phosphate (r = 0.73), nitrite and nitrate (r = 0.71), temperature and DO (r = - 0.73), DO and phosphate (r = - 0.50), pH and ammonia (r = - 0.71), as well as phosphate and nitrate (r = -0.55). These results indicate that physico-chemical properties should be taken into account during the development of management strategies to protect the Egyptian marine environment, especially in the Red sea areas.
The accuracy of cerebellar diameter in detection of the expected date of delivery in comparison with femur length in third trimester

The accuracy of cerebellar diameter in detection of the expected date of delivery in comparison with femur length in third trimester Abstract Background: The cerebellum, the largest part of hind brain, lies in the posterior cranial fossa. In the embryo cerebellum appears at the end of the fifth week as a swelling overriding the fourth ventricle. Assessment of gestational age (G.A.) is important in the management of pregnancy. The aim is to assess the reliability of trans-cerebellum diameter in compare with the femur length in predicting gestational age. Methodology: This is descriptive, cross-sectional study carried out on seventy-one pregnant women with history of reliable menstrual cycles (sure of dates, regular cycles, no history of hormonal contraception at last 6 months, no history of abortion or delivery at last 3 months) and did not suffer from any complications for the mother or fetus, referred for routine ultrasound examination in ultrasound department of El Minia University maternity hospital, FL was used as standard method to estimate gestational age to be compared with the other gestational age that obtained with TCD. Results: among pregnant women in the GA 28-32 and 32-36 weeks, there was non-statistically significant difference between GA as estimated by TCD and as estimated by other assessed fetal biometry (SFH and FL). we found that TCD can correctly predict GA in early 3 rd trimester (28-36 weeks) at cut-off point >34.9 mm with a sensitivity of 94%. Conclusions: The result of the study revealed that is there is no significant difference between gestational age obtained with FL and TCD. The study recommended that the TCD can be used as routine measurement in estimation of the gestational age in the third trimester.
New physics in inclusive semileptonic B decays including nonperturbative corrections

In this work, we study the effects of New Physics (NP) operators on the inclusive [Formula: see text] decay including power [Formula: see text] corrections in the NP operators. In analogy with [Formula: see text] observables, we study the observable [Formula: see text]. We present some numerical results for [Formula: see text] and compare the results for this observable with and without power corrections in the NP contributions.
VIRTUAL MIMO FOR VEHICULAR COMMUNICATION SYSTEMS

This paper provides a simulation study for the quality of vehicle communication system by using a Virtual Multiple-Input Multiple-Output (VMIMO) used in Ultrawide Band (UWB) wireless communication, merged with orthogonal pulse shaping using modified Hermite polynomial. The simulation compares between Zero-Forcing (ZF) and Minimum Square Error (MMSE) Detection Techniques performance through bit-error-rate analysis. The simulation includes different scenarios for vehicular communication: The Vehicle to Vehicle (V2V) and the Vehicle to Infrastructure (V2I). Firstly, the Non-Line-of-Sight (NLOS), secondly the Line-of-Sight (LOS) scenarios. Moreover, the simulation considers the effect of path-loss and noise on transmitted signal, besides the comparison with QAM (Quadratic amplitude modulation), QPSK (quadratic pulse shift keying) and (Binary pulse shift keying) BPSK modulations. The simulation result is useful for the design of vehicle communication system including several cases of vehicles communication such as the V2V and V2I. The final results recommend BPSK-MMSE communication for both the LOS and NLOS scenarios for the V2V and V2I.
Degradation of methyl orange by persulfate activated with magnetically separatable CuFe2O4/RGO nanocomposites: efficiency, stability, and synergy

A facile method was used to synthesize CuO/reduced graphene oxide (CuO/RGO), Fe 3 O 4 /RGO and CuFe 2 O 4 /RGO nanocomposites (NCs) by co-precipitation of graphene oxide (GO) with copper and iron salts in one-pot at 190°C. The structures, compositions, purities, and morphologies of these NCs were analyzed by scanning electron microscopy, X-ray diffraction, X-ray photoelectron spec- troscopy, and Fourier transform infrared spectroscopy techniques. The results show that CuO, Fe 3 O 4 and CuFe 2 O 4 nanoparticles decorated uniformly the RGO sheets. The prepared NCs were employed as heterogeneous persulfate activators for the degradation of methyl orange (MO), as a model pollutant. The effects of some key parameters including sodium persulfate (SPS) dosage, activator dosage, initial pH value, and reaction time on MO degradation were investigated. Under the opti-mized conditions of 5 mM SPS dosage, 1.0 g/L activator dosage at an initial solution pH of 4, 100%, 82.5% and 78.6% of MO could be removed within 90 min in the CuFe 2 O 4 /RGO, CuO/RGO and Fe 3 O 4 / RGO systems, respectively. The CuFe 2 O 4 /RGO NCs exhibited higher efficiency, better reusability and wider pH range for MO degradation than CuO/RGO and Fe 3 O 4 /RGO NCs, implying the iron-copper synergy in the material. Especially, the CuFe 2 O 4 /RGO NCs exhibited good magnetic separa- tion performance, which favored its recovery and reuse from aquatic environment. The quenching experiments suggest that sulfate radicals were the dominant reactive species.
Optical encoder neural network: a CNN-based optical encoder for robot localization

Abstract. We tackle the problem of robot localization by means of a deep learning (DL) approach. Convolutional neural networks, mainly devised for image analysis, are at the core of the proposed solution. An optical encoder neural network (OE-net) is devised to give back the relative pose of a robot by processing consecutive images. A monocular camera, fastened on the robot and oriented toward the floor, collects the vision data. The OE-net takes a pair of the acquired consecutive images as input and provides the relative pose information. The neural network is trained using a supervised learning approach. This preliminary study, made on synthetic images, suggests that a convolutional network and hence a DL approach can be a viable complement to the traditional visual odometry for robot ego-motion estimation. The obtained outcomes look very promising.
Influence of some Storage Conditions on Grain Quality Characters of some Egyptian Rice Cultivars

Two experiments were performed at Rice Technology Training Center (RTTC, Field crop Research Institute, Agricultural Research Center (ARC) , Egypt, to decide the impact of storage periods (3, 6, 9 and 12 months), type of bags (jute, paper, stripped plastic and polyethylene) and their interaction on grain quality characters of rice cultivars. Newly harvested certified seeds in 2018 and 2019 seasons of three rice cultivars namely, Sakha 101 as japonica cultivars, Giza 178 as indica/ japonica cultivars, and Egyptian Yasmin as indica cultivars were provided by Rice Research Program, Agriculture Research Center, Sakha, Kafr El-Sheikh, Egypt. A split- split plot design with three replicates was used. The most noteworthy qualities for hulling % and milling % by keeping Sakha 101 for 3 months in jute bags in both seasons. Furthermore, data revealed that keeping Egyptian Yasmin for year in polyethylene bags showed predominance values for broken %, amylose content % and protein content % in both study seasons. Most elevated values for elongation % and water uptake were realized by keeping Egyptian Yasmin for year in jute bags in both seasons. Most elevated values for gel consistency were recorded by keeping Sakha 101 for year in jute bags while; the most noteworthy values for spreading and clearing were realized by keeping Sakha 101 for 3 months in polyethylene bags in both seasons. We recommend to store paddy rice in jute bags for getting best quality rice.
THE EFFECT OF PLANETS BEYOND THE ICE LINE ON THE ACCRETION OF VOLATILES BY HABITABLE-ZONE ROCKY PLANETS

Models of planet formation have shown that giant planets have a large impact on the number, masses, and orbits of terrestrial planets that form. In addition, they play an important role in delivering volatiles from material that formed exterior to the snow line (the region in the disk beyond which water ice can condense) to the inner region of the disk where terrestrial planets can maintain liquid water on their surfaces. We present simulations of the late stages of terrestrial planet formation from a disk of protoplanets around a solar-type star and we include a massive planet (from 1 M⊕ to 1 MJ) in Jupiter's orbit at ∼5.2 AU in all but one set of simulations. Two initial disk models are examined with the same mass distribution and total initial water content, but with different distributions of water content. We compare the accretion rates and final water mass fraction of the planets that form. Remarkably, all of the planets that formed in our simulations without giant planets were water-rich, showing that giant planet companions are not required to deliver volatiles to terrestrial planets in the habitable zone. In contrast, an outer planet at least several times the mass of Earth may be needed to clear distant regions of debris truncating the epoch of frequent large impacts. Observations of exoplanets from radial velocity surveys suggest that outer Jupiter-like planets may be scarce, therefore, the results presented here suggest that there may be more habitable planets residing in our galaxy than previously thought.
Floquet engineering in superconducting circuits: From arbitrary spin-spin interactions to the Kitaev honeycomb model

We derive a theory for the generation of arbitrary spin-spin interactions in superconducting circuits via periodic time modulation of the individual qubits or the qubit-qubit interactions. The modulation frequencies in our approach are in the microwave or radio-frequency regime, so the required fields can be generated with standard generators. Among others, our approach is suitable for generating spin lattices that exhibit quantum spin liquid behavior such as Kitaev's honeycomb model.
Mesenchymal stem cells and Cryopreservation, a new concept

Recently, there has been an increasing interest in the study of mesenchymal stem cells (MSCs), which are considered as subtype of adult stem cells with the ability of differentiation into ectoderm (into neural cells), endoderm (into hepatocytes, insulin B producing cells) or mesoderm (into adipocytes, osteocytes, chondrocytes), this was associated with increased clinical application of such cells in the management of autoimmune diseases such as (Type 1 diabetes and Rheumatoid arthritis), degenerative diseases as (Parkinson‟s disease, Amylotrophic lateral sclerosis, and Alzheimer) and inflammatory diseases, and consequently increased the need for and effective and safe way of preservation of these cells for a long time without affecting the viability of the MSCs after the long-term preservation. This review discusses criteria of mesenchymal stem cells (MSCs), their markers, sources, methods of isolation and culturing, and their clinical applications, and then it discusses types of cryopreservation of MSCs and factors that may have an influence on viability of MSCs following the process of cryopreservation.
Processing Induced Voxel Correlation in SENSE FMRI Via the AMMUST Framework

Daniel B. Rowe and Iain P. Bruce Department of Math, Stat, and Comp Sci, Marquette University, Milwaukee, Wisconsin, USA Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA Introduction: It is well known that magnetic field gradients can be used to Fourier encode the complex-valued spatial frequencies of an object. From a two dimensional array of the complex-valued spatial frequencies for an object SC, a complex-valued image VC can be reconstructed via inverse Fourier transform as
Using Kepler transit observations to measure stellar spot belt migration rates

Planetary transits provide a unique opportunity to investigate the surface distributions of star spots. Our aim is to determine if, with continuous observation (such as the data that will be provided by the Kepler mission), we can in addition measure the rate of drift of the spot belts. We begin by simulating magnetic cycles suitable for the Sun and more active stars, incorporating both flux emergence and surface transport. This provides the radial magnetic field distribution on the stellar surface as a function of time. We then model the transit of a planet whose orbital axis is misaligned with the stellar rotation axis. Such a planet could occult spots at a range of latitudes. This allows us to complete the forward modelling of the shape of the transit light curve. We then attempt the inverse problem of recovering spot locations from the transit alone. From this we determine if transit light curves can be used to measure spot belt locations as a function of time. We find that for low-activity stars such as the Sun, the 3.5-year Kepler window is insufficient to determine this drift rate. For more active stars, it may be difficult to distinguish subtle differences in the nature of flux emergence, such as the degree of overlap of the ‘butterfly wings’. The rate and direction of drift of the spot belts can however be determined for these stars. This would provide a critical test of dynamo theory.
Measurement of block-diagonal scattering matrix

The problem of measurement of the block-diagonal scattering matrix is addressed. It has been shown that non-zero elements of the scattering matrix with block-diagonal structure can be measured using only two polarizations of input radiation. Optimal pairs of these polarizations are derived. Utilization of the optimal input polarization results in half the measurement time and a decrease in measurement errors of approximately 30%.
Influence of Honey Addition As a Natural Energy Source On Cooled Camel Spermatozoa

: Camel is an important source of food as well as of transport for large communities in sub-Saharan Africa, the Middle East, and the Indian subcontinent. The present study aimed to evaluate the effect of different concentrations of honey (0.0, 1.0, 2.5, or 5.0%) addition to Tris-extender on epididymal camel semen quality during storage at 5º C for up to 48 hrs. Eleven healthy dromedary camels ( Camelus dromedarius ), aged between 8 to 15 years, were used in the present study during the rutting season. Percentages of sperm motility, dead spermatozoa, abnormal spermatozoa, acrosome damage, and membrane integrity were determined. The obtained results showed that the extended semen supplemented with honey at levels of 1%, and 2.5% significantly (P<0.01) improved percentages of sperm motility, intact acrosome, and membrane integrity, while decreased the percentages of dead and abnormal camel spermatozoa during storage at 5ºC for up to 48 hrs. Moreover, the addition of 5.0% honey to the extender significantly (P<0.01) tended to be a deleterious effect on camel semen quality. In conclusion, Tris-extender added with 2.5% honey improved camel semen quality during storage at 5º C for up to 48 hrs.
Smart bin: Waste segregation system using deep learning‐Internet of Things for sustainable smart cities

Waste management is a major issue with the emerging growth in the world population, and we need to find efficient ways to recycle and reuse waste. Segregating waste has become a primary need in waste management as different types of waste like Bio & Non‐Bio‐degradable waste should be processed differently. Effective waste isolation at the fundamental level is especially required for this. Several Smart cities oriented smart garbage management systems are also proposed using Internet of Things (IoT) and GSM. The existing smart bins using IoT and wireless sensor network (WSN) are dependent significantly on two major things. First, multiple types of sensors, as a single sensor may not be able to detect different material waste, and second, the console (Microcontroller, Arduino Raspberry Pi) and connectivity which in turn dependent on programming and operating system. These limitations of the embedded smart bin are overcome by combining IoT with artificial intelligence approaches such as deep neural network (DNN) systems. In this paper, we have presented a Friendly Waste Segregator Using Deep Learning and the IoT to classify and isolate the waste objects as biodegradable and nonbiodegradable. Our proposed method utilizes, a robust deep learning network to classify the waste accurately and IoT for monitoring and connectivity using various sensors. Our proposed method with initial training can identify and segregte real‐time waste objects without human intervention with an average accuracy of 97.49 %. Our smart bin intends to provide optimized waste management of bio and non‐bio‐waste and help to build an ecologically safe society.
A Hybrid Recommender System Combining Collaborative Filtering with Utility Mining

: Based on a variety of information sources, recommender systems can identify specific items for various user interests. Techniques for recommender systems are classified into two types: personalized and non-personalized. Personalized algorithms are based on individual user preferences or collaborative filtering data; as the system learns more about the user, the recommendations will become more satisfying. They do, however, suffer from data sparsity and cold start issues. On the other hand, non-personalized algorithms make recommendations based on the importance of the items in the database; they are very useful when the system has no information about a specific user. Their accuracy, however, is limited by the issue of personalization. In most cases, one of the recommendation categories can be used to make recommendations. Yet, it is a challenge to evaluate the importance of items to the user while simultaneously using personalized and non-personalized preferences functions and ranking a set of candidate items based on these functions. This paper addresses this issue and improves recommendation quality by introducing a new hybrid recommendation technique. The proposed hybrid recommendation technique combines the importance of items to the user obtained by the utility mining method with the similarity weights of items produced by the collaborative filtering technique to make the recommendation process more reasonable and accurate. This technique can provide appropriate recommendations whether or not users have previous purchasing histories. Finally, experimental results show that the proposed hybrid recommendation technique outperforms both implemented collaborative filtering and utility-based recommendation techniques.