Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Detection Limits in Magnetic Nanoparticle Enhanced Microwave Imaging

Magnetic nanoparticles-aided microwave imaging is an emerging modality for the diagnosis of early stage tumors. It exploits the possibility of modulating the response at microwaves of magnetic nanoparticles, employed as contrast agent selectively accumulated into the tumor. In this paper, we describe the results of an experimental study aimed at establishing the actual detection limits of the approach, namely the minimum amount of magnetic nanoparticles to be delivered for a reliable imaging. The assessment is carried out on breast phantoms made of ex-vivo minced pig tissues and using commercially available magnetic nanoparticles. The results show that it is possible to detect amounts of magnetic nanoparticles between 2 and 7 mg, dispersed in a volume of about one cubic centimeter, depending on the breast type. While such quantities are already consistent with those currently reachable via active selective targeting, an in-depth analysis of the results allows to identify strategies to further lower the detection limits up to four times, by refining the measurement set-up and setting the amplitude of the polarizing magnetic field modulating the nanoparticle response to a suitable value.
Fuzzy Logic Energy Management System in Islanded Hybrid Energy Generation Microgrid

The aim of this paper is to project and simulate an energy management system which has application in a real-life hybrid energy generation microgrid. Both rule-based and fuzzy logic control systems are simulated using MATLAB/Simulink. The control strategies are compared in regards to diesel generator usage, storage system charge and discharge behavior and the overall system energy balance.
Mucosal-Associated Invariant T Cells Improve Nonalcoholic Fatty Liver Disease Through Regulating Macrophage Polarization

Mucosal-associated invariant T (MAIT) cells, a novel population of innate-like lymphocytes, have been involved in various inflammatory and autoimmune diseases. However, their role in the development of nonalcoholic fatty liver disease (NAFLD) remains unclear. In this study, we investigated the alterations of phenotype and immunological function of MAIT cells in NAFLD. Analysis of PBMCs in 60 patients with NAFLD and 48 healthy controls (HC) revealed that circulating MAIT cell frequency decreased in NAFLD, especially in the patients with higher serum levels of γ-glutamyl transferase or total triglyceride. Functional alterations of circulating MAIT cells were also detected in NAFLD patients, such as the increased production of IL-4 whereas the decreased production of IFN-γ and TNF-α. Furthermore, elevated expression of CXCR6 was observed in circulating MAIT cells of patients. Meanwhile, we found an increased number of MAIT cells in the livers of NAFLD, and the number was even greater in patients with higher NAFLD activity score. Moreover, activated MAIT cells induced monocytes/macrophages differentiation into M2 phenotype in vitro. Additionally, MAIT cells were enriched and displayed Th2 type cytokines profile in livers of wild type mice fed with methionine and choline deficient diet (MCD). Notably, mice deficient of MAIT cells exhibited more severe hepatic steatosis and inflammation upon MCD, accompanied with more CD11c+ proinflammatory macrophages (M1) and less CD206+ anti-inflammatory macrophages (M2) in livers. Our results indicate that MAIT cells protect against inflammation in NAFLD through producing regulatory cytokines and inducing anti-inflammatory macrophage polarization, which may provide novel therapeutic strategies for NAFLD.
Dietary folate intake and pancreatic cancer risk: Results from the European prospective investigation into cancer and nutrition

Pancreatic cancer (PC) has an exceptionally low survival rate and primary prevention strategies are limited. Folate plays an important role in one‐carbon metabolism and has been associated with the risk of several cancers, but not consistently with PC risk. We aimed to investigate the association between dietary folate intake and PC risk, using the standardised folate database across 10 European countries. A total of 477,206 participants were followed up for 11 years, during which 865 incident primary PC cases were recorded. Folate intake was energy‐adjusted using the residual method. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. In multivariable analyses stratified by age, sex, study centre and adjusted for energy intake, smoking status, BMI, educational level, diabetes status, supplement use and dietary fibre intake, we found no significant association between folate intake and PC risk: the HR of PC risk for those in the highest quartile of folate intake (≥353 μg/day) compared to the lowest (<241 μg/day) was 0.81 (95% CI: 0.51, 1.31; ptrend = 0.38). In current smokers, a positive trend was observed in PC risk across folate quartiles [HR = 4.42 (95% CI: 1.05, 18.62) for ≥353 μg/day vs. <241 μg/day, ptrend = 0.01]. Nonetheless, there was no significant interaction between smoking and dietary folate intake (pinteraction = 0.99). We found no association between dietary folate intake and PC risk in this large European study.
Energy Efficient Resource Optimization for a Downlink NOMA Heterogeneous Small-Cell Network

Non-orthogonal multiple access (NOMA) is considered to be a key technology for fifth-generation mobile communication networks due to its superior spectral efficiency. In this paper, the problem of energy efficient subchannel and power allocation is investigated for a downlink NOMA heterogeneous network. The energy efficient resource allocation problem is first formulated as a mixed integer nonconvex optimization problem. By exploiting convex relaxation and dual decomposition techniques, a closed-form expression is derived via a Lagrangian approach. Simulation results show that the proposed algorithm can converge within ten iterations and obtain high system energy efficiency.
Energy Efficient Resource Allocation for Energy Harvesting Aided H-CRAN

With an exponentially increasing number of users and their data rate demands, current 4G cellular networks need to be evolved to next fifth-generation networks. A heterogeneous cloud radio access network (H-CRAN) is the promising architecture for future high data rate enabled, energy efficient networks. The H-CRAN differs from today’s cellular system by addition of an extra number of remote radio heads (RRHs) within the vicinity of one macro base station. This provides high data rates to users with minimized interference by centrally controlling the resource allocation. On the other hand, increased density of hardware in the area, the H-CRAN also consumes more grid power of the system. To mitigate the greater power requirements for this type of a dense network, energy harvesting (EH) techniques are used to minimize the consumption of grid power. In EH, energy is harvested from ambient sources, such as solar and wind. By maximizing the harvested energy usage instead of grid power, the system’s energy efficiency (EE) can be improved significantly. In this paper, the EE of an H-CRAN consisting of several green RRHs powered by EH modules is explored. A mixed integer non-linear programming problem is formulated, which maximizes the EE of the system. A mesh adaptive direct search algorithm is used to optimize the problem. As a result of this optimization, efficient power and resource allocation are done and higher EE is achieved with low complexity and lower consumption of grid power.
Image Enhancement Based on Region-Based Contraction Process

In this paper, we propose a region-based contraction process for image enhancement. At the beginning, the input image is converted into HSV color space to preserve the hue and saturation information. The brightness V is separated into 256 levels of regions. After that, we add in two pseudo regions with the brightness values 0 and 255 and our image enhancement algorithm pulls the brightness of image regions forward 0 or 255 based on a region-based contraction process. Experimental results show that the proposed process provides an effective and efficient way to implement image enhancement.
HDGM: Hierarchical Dynamic Goal Management for Many-Core Resource Allocation

Many-core systems are highly complex and require thorough orchestration of different goals across the computing abstraction stack to satisfy embedded system constraints. Contemporary resource management approaches typically focus on a fixed objective, while neglecting the need for replanning (i.e., updating the objective function). This trend is particularly observable in existing resource allocation and application mapping approaches that allocate a task to a tile to maximize a fixed objective (e.g., the cores’ and network’s performance), while minimizing others (e.g., latency and power consumption). However, embedded system goals typically vary over time, and also over abstraction levels, requiring a new approach to orchestrate these varying goals. We motivate the problem by showcasing conflicts resulting from state-of-the-art fixed-objective resource allocation approaches, and highlight the need to incorporate dynamic goal management from the very early stages of design. We then present the concept of a hierarchical dynamic goal manager that considers the priority, significance, and constraints of each application, while holistically coupling the overlapping and/or contradicting goals of different applications to satisfy embedded system constraints.
Effects of early postoperative enteral nutrition versus usual care on serum albumin, prealbumin, transferrin, time to first flatus and postoperative hospital stay for patients with colorectal cancer: A systematic review and meta-analysis

Background: Early enteral nutrition (EEN) after surgery had been reported to decrease morbidity and mortality. However, no meta-analysis performed on nutrition status and recovery after surgery to Colorectal cancer (CRC). Aim: We aimed to estimate effect of EEN for postoperative CRC. Methods: Electronic databases were searched for randomized controlled trials published prior to September 2017. Papers comparing EEN after surgery to traditional nutritional regimen in CRC patients were selected. The chosen articles should containe one or more of the following outcome measures: serum albumin, prealbumin, transferrin, time to first flatus and postoperative hospital stay. Results: 2307 cases from 26 studies were included. The analysis showed that EEN was more effective in increasing serum albumin and prealbumin, promoting the recovery of gastrointestinal function, and decreasing the time of postoperative hospital stay, especially for colon cancer. Conclusion: EEN can improve nutritional status and promote intestinal function recovery for patients undergoing CRC surgery.
Multidimensional assessment of impulsivity-related measures in relation to externalizing behaviors

Abstract Background Trait impulsivity is thought to play a key role in predicting behaviors on the externalizing spectrum, such as drug and alcohol use and aggression. Research suggests that impulsivity may not be a unitary construct, but rather multidimensional in nature with dimensions varying across self-report assessments and laboratory behavioral tasks. Few studies with large samples have included a range of impulsivity-related measures and assessed several externalizing behaviors to clarify the predictive validity of these assessments on important life outcomes. Methods Community adults (N = 1295) between the ages of 30 and 54 completed a multidimensional assessment of impulsivity-related traits (including 54 self-report scales of personality traits implicated in impulsive behaviors, and four behavioral tasks purporting to assess a construct similar to impulsivity) and reported on five externalizing behavioral outcomes (i.e. drug, alcohol, and cigarette use, and physical and verbal aggression). We ran an exploratory factor analysis on the trait scales, and then a structural equation model predicting the externalizing behaviors from the three higher-order personality factors (i.e. Disinhibition v. Constraint/Conscientiousness, Neuroticism/Negative Emotionality, and Extraversion/Positive Emotionality) and the four behavioral tasks. Results Relations between the self-report factors and behavioral tasks were small or nonexistent. Associations between the self-report factors and the externalizing outcomes were generally medium to large, but relationships between the behavioral tasks and externalizing outcomes were either nonexistent or small. Conclusions These results partially replicate and extend recent meta-analytic findings reported by Sharma et al. (2014) to further clarify the predictive validity of impulsivity-related trait scales and laboratory behavioral tasks on externalizing behaviors.
The actinobacterial WhiB‐like (Wbl) family of transcription factors

The WhiB‐like (Wbl) family of proteins are exclusively found in Actinobacteria. Wbls have been shown to play key roles in virulence and antibiotic resistance in Mycobacteria and Corynebacteria, reflecting their importance during infection by the human pathogens Mycobacterium tuberculosis, Mycobacterium leprae and Corynebacterium diphtheriae. In the antibiotic‐producing Streptomyces, several Wbls have important roles in the regulation of morphological differentiation, including WhiB, a protein that controls the initiation of sporulation septation and the founding member of the Wbl family. In recent years, genome sequencing has revealed the prevalence of Wbl paralogues in species throughout the Actinobacteria. Wbl proteins are small (generally ~80–140 residues) and each contains four invariant cysteine residues that bind an O2‐ and NO‐sensitive [4Fe–4S] cluster, raising the question as to how they can maintain distinct cellular functions within a given species. Despite their discovery over 25 years ago, the Wbl protein family has largely remained enigmatic. Here I summarise recent research in Mycobacteria, Corynebacteria and Streptomyces that sheds light on the biochemical function of Wbls as transcription factors and as potential sensors of O2 and NO. I suggest that Wbl evolution has created diversity in protein–protein interactions, [4Fe–4S] cluster‐sensitivity and the ability to bind DNA.
A Case Study for Five Phase Induction Motor Design: Evaluation Using Finite Element Analysis

The Multiphase machine coupled with multiphase converters can be a candidate for adjustable speed drives where the machine can have the same control principal as conventional three-phase but it is superior from fault tolerant capability aspect. Numerous research topics deal with multiphase machines are introduced, specifically five-phase. One of the research topics is the machine design. The design procedure starts by finding motor dimensions, winding dimensions for both stator and rotor. Second step is to the motor parameters. Lastly, the design should be evaluated through the motor performance using both analytical and numerical techniques. A case study of designing a 3 hp five-phase induction motor, is introduced to the same conference two parts where part I covers the dimensions side and part II covers the performance evaluation for the designed motor using analytical technique (MA TLAB/ SIMULINK). The target of this paper is to assess the designed motor and investigate the performance using numerical technique such Finite Elements, (FE).
Market Chain Analysis of Cotton the Case of Arbaminch Zuria District, Gamo Gofa Zone, Ethiopia

Ethiopia is believed to be one of the origins of cotton, and cotton cultivation is deep-rooted in the history of the country’s agriculture. It is one of the major cash crops in the country and is extensively grow in the lowlands under large-scale irrigation schemes and also it is grow on small-scale farms under rainfed agriculture. The economic value of cotton in the Ethiopian economy is significant. Firstly, it is a major industrial input for textile firms. The textile and garment industry is one of the priority areas in Ethiopia’s industrial policy. Secondly, cotton is a major export crop [1]. However, Ethiopia share only about 5% of total cotton produced in Africa [2]. As to total arable and potential area for cotton production, the country is utilizing below potential. According to Bosena et al. [3], out of the country’s total potential areas for cotton production, only about 4% is being utilized. As a result, the amount of cotton produced in the country is low. Cotton is grow in many regions in the country. In each region, there are wide potential areas. Gamo Gofa zone is the second largest cotton growing region in the country after the Amhara Region [4]. However, most studies which have been conducted on cotton marketing [1-3,5] were limited to a specific (Awash Valley, Humera, Metema and Abobo) areas. This study was designed to analyze cotton market chain to generate information about its entire market chain in the study area due to absence of adequate information on cotton market channel, market structure, conduct and performance cotton marketing had been a challenge for the farmers as they were getting low prices from the local middlemen [6]. Having these evidences, cotton market chain analysis is conducted in Arbaminch Zuria District of Gamo Gofa zone with the specific objectives of analyzing cotton market channel, market structure, and conduct performance and to analyze factors affecting market supply of cotton at farm level.
Fast analytical evaluation of intermolecular electrostatic interaction energies using the pseudoatom representation of the electron density. I. The Löwdin α-function method.

The previously reported [Volkov et al. (2004). Chem. Phys. Lett. 391, 170-175] exact potential and multipole moment (EP/MM) method for evaluation of intermolecular electrostatic interaction energies using the nuclei-centered pseudoatom representation of electron densities is significantly improved in terms of both speed and accuracy by replacing the numerical quadrature integration of the exact potential with a fully analytical technique. The resulting approach, incorporated in the XDPROP module of the software package XD, has been tested on several molecular systems ranging in size from water-water to dodecapeptide-dodecapeptide dimers using electron densities constructed via the University at Buffalo Aspherical Atom Databank. The improved hybrid method provides electrostatic interaction energies within the uncertainty of ≤0.2 kJ mol-1 for all benchmark systems. The running time for a dimer of a sizable, 225-atom dodecapeptide is under 4 s on a 2012 central processing unit (2.8 GHz AMD Opteron 6348) and under 3 s on a relatively modern processor (2.8 GHz Intel Xeon E3-1505M v5).
Morbidity pattern and outcome of patients admitted in a coronary care unit: a report from a secondary hospital in southern region, Saudi Arabia

ABSTRACT Background: There is limited information about the clinical profile and outcome on patients admitted to a coronary care unit (CCU) in Saudi Arabia is available. Objective: The aim of this study was to evaluate reasons for admission, clinical characteristics, outcome and predictors of outcome in CCU patients. Materials and methods: The data of 392 patients admitted to the CCU of a secondary care centre in southern region of Saudi Arabia from 1 January 2017 to 31 December 2017 were collected. Data that were extracted from the patients included demographics, admission diagnosis and outcome. Results: A total of 392 patients, comprising 305 (77.81%) males and 87 (22.19%) females, were admitted to the CCU. Their mean age was 64.62 ± 15.7. The most common cause of admission was acute coronary syndrome (63.3%), the majority (97.2%) of whom were above 50 years of age (Table 2). Thirty-one patients died. This figure accounted for 7.7% of all the patients admitted to the CCU and 23.4% of the patients that were fully managed in the CCU. The majority of the patients that died were those with cardiac arrest (12 out of 16). Acute coronary syndrome (p = 0.029), cardiac arrest (p = 0.000) and age greater than 50 years (p = 0.000) were associated with death in the study patients. However, cardiac arrest (p = 0.002) and age greater than 50 years (p = 0.017) were independent predictors of death in the study patients. Conclusion: The reasons for admission to the CCU were acute coronary syndrome, heart failure and cardiac arrest. Mortality among CCU patient was comparable to reports elsewhere. Cardiac arrest and age greater than 50 years were independent predictors of death.
Regulatory network of genes associated with stimuli sensing, signal transduction and physiological transformation of appressorium in Magnaporthe oryzae

ABSTRACT Rice blast caused by Magnaporthe oryzae is the most destructive disease affecting the rice production (Oryza sativa), with an average global loss of 10–30% per annum. Recent reports have indicated that the fungus also inflicts blast disease on wheat (Triticum aestivum) posing a serious threat to the wheat production. Due to its easily detected infectious process and manoeuvrable genetic manipulation, M. oryzae is considered a model organism for exploring the molecular mechanism underlying fungal pathogenicity during the pathogen–host interaction. M. oryzae utilises an infectious structure called appressorium to breach the host surface by generating high turgor pressure. The appressorium development is induced by physical and chemical cues which are coordinated by the highly conserved cAMP/PKA, MAPK and calcium signalling cascades. Genes involved in the appressorium development have been identified and well studied in M. oryzae, a summary of the working gene network linking stimuli sensing and physiological transformation of appressorium is needed. This review provides a comprehensive discussion regarding the regulatory networks underlying appressorium development with particular emphasis on sensing of appressorium inducing stimuli, signal transduction, transcriptional regulation and the corresponding developmental and physiological responses. We also discussed the crosstalk and interaction of various pathways during the appressorium development.
UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation

This paper presents a deep network based unsupervised visual odometry system for 6-DoF camera pose estimation and finding dense depth map for its monocular view. The proposed network is trained using unlabeled binocular stereo image pairs and is shown to provide superior performance in depth and ego-motion estimation compared to the existing state-of-the-art. This is achieved by introducing a novel objective function and training the network using temporally alligned sequences of monocular images. The objective function is based on the Charbonnier penalty applied to spatial and bi-directional temporal reconstruction losses. The overall novelty of the approach lies in the fact that the proposed deep framework combines a disparity-based depth estimation network with a pose estimation network to obtain absolute scale-aware 6-DoF camera pose and superior depth map. According to our knowledge, such a framework with complete unsupervised end-to-end learning has not been tried so far, making it a novel contribution in the field. The effectiveness of the approach is demonstrated through performance comparison with the state-of-the-art methods on KITTI driving dataset.