Miracle-dz/UniFAR-FTUs huggingface dataset:
Implication of Trimethylamine N-Oxide (TMAO) in Disease: Potential Biomarker or New Therapeutic Target

Trimethylamine N-oxide (TMAO) is a molecule generated from choline, betaine, and carnitine via gut microbial metabolism. The plasma level of TMAO is determined by several factors including diet, gut microbial flora, drug administration and liver flavin monooxygenase activity. In humans, recent clinical studies evidence a positive correlation between elevated plasma levels of TMAO and an increased risk for major adverse cardiovascular events. A direct correlation between increased TMAO levels and neurological disorders has been also hypothesized. Several therapeutic strategies are being explored to reduce TMAO levels, including use of oral broad spectrum antibiotics, promoting the growth of bacteria that use TMAO as substrate and the development of target-specific molecules. Despite the accumulating evidence, it is questioned whether TMAO is the mediator of a bystander in the disease process. Thus, it is important to undertake studies to establish the role of TMAO in human health and disease. In this article, we reviewed dietary sources and metabolic pathways of TMAO, as well as screened the studies suggesting possible involvement of TMAO in the etiology of cardiovascular and neurological disorders, underlying the importance of TMAO mediating inflammatory processes. Finally, the potential utility of TMAO as therapeutic target is also analyzed.
Filterless and Semi-Filterless Solutions in a Metro-HAUL Network Architecture

Filterless optical networks based on broadcast-and-select nodes have been proven to be a cost-effective alternative to active photonic network solutions in core networks. However, due to the emergence of novel metro-based high-bandwidth cloud-based services (e.g., Virtual Reality, 4K Video-on-Demand, etc.), filterless solutions have started to attract research attention also in the metro area. In this paper, we evaluate the performance of fully-filterless and semi-filterless (i.e., hybrid solutions between fully-filterless and active photonic architectures) optical-network architectures in terms of cost of network elements and spectrum utilization, in a metro-network scenario. Our evaluations show that, due to the ring-based hierarchical nature of metro networks, fully-filterless architectures tend to require excessive spectrum utilization as the broadcast effect spreads among all hierarchical rings. On the contrary, semi-filterless network architectures seem more promising due to the presence of filters that fend off the propagation of unfiltered channels. The results also show that it is more advantageous to deploy filters at nodes of the lower network levels than at nodes of higher network levels.
Design and Comparative Analysis of Mobile Computing Software Framework

Mobile computing is human-computer cooperation by which a computer is relied upon to be transported amid typical use, which considers transmission of information, voice and video. Mobile computing includes mobile hardware and mobile software. Hardware incorporates mobile gadgets or gadget segments. Mobile software manages the attributes and necessities of mobile applications. These hardware and software parts integrates into operating system. Each cell phones keep running on some sort of Operating System. The Operating System could possibly get refreshes from the producer. Mobile operating systems play out an extensive arrangement of errands which are typically chosen by the seller building up the product. Our undertaking points is to plan an OS which will decrease the symptoms of having unnecessary forms working in the back ground over which clients would for the most part have no control. TOn the off chance that we prevail with our target of building up a completely free advanced android OS, it would help us to figure out which bundles ought to be permitted to be introduced to the cell phone. It would likewise help us to remain furiously autonomous to the extent programming assets related with mobile phones are considered. Thus mobile computing challenges can be solved to a great extend.
A Zero-Day Resistant Malware Detection Method for Securing Cloud Using SVM and Sandboxing Techniques

Cloud nowaday has become the backbone of the IT infrastructure. Whole of the infrastructure is now being shifted to the clouds, and as the cloud involves all of the networking schemes and the OS images, it inherits all of the vulnerabilities too. And hence securing them is one of our very prior concerns. Malwares are one of the many other problems that have ever growing and hence need to be eradicated from the system. The history of mal wares go long back in time since the advent of computers and hence a lot of techniques has also been already devised to tackle with the problem in some or other way. But most of them fall short in some or other way or are just too heavy to execute on a simple user machine. Our approach devises a 3 - phase exhaustive technique which confirms the detection of any kind of malwares from the host. It also works for the zero-day attacks that are really difficult to cover most times and can be of really high-risk at times. We have thought of a solution to keep the things light weight for the user.
Single-Chip Gen2-Compliant UHF RFID Sensor Tags Based on Novel Pseudo-BAP Mode

In this work a new design strategy for UHF RFID tags mounting RFID chips with embedded sensor is proposed. In particular, a novel functioning mode named “Pseudo-BAP” is introduced to solve the electromagnetic “filed-off’ problem and to allow for a fully Gen2-compliant tag interrogating sequence to retrieve sensor data. In particular, a prototype of Pseudo-BAP-empowered Tag testing board has been designed, fabricated in FR4 and fully tested from the electromagnetic point of view. At the end, the proposed approach allows for the passive RFID-based temperature data collection from sensor-provided RFID chips by using standard RFID readers, and appreciable working distances as large as 1.75 m have been obtained with the considered low-sensitivity chip.
Neurology Care, Diagnostics, and Emerging Therapies of the Patient With Duchenne Muscular Dystrophy

Building on the 2018 Duchenne Muscular Dystrophy Care Considerations, we provide detailed guidance on neurology management, diagnostics, and emerging therapies for patients with DMD. Duchenne muscular dystrophy is the most common form of childhood muscular dystrophy. A mutation in the DMD gene disrupts dystrophin (protein) production, causing damage to muscle integrity, weakness, loss of ambulation, and cardiopulmonary compromise by the second decade of life. Life expectancy has improved from mid-teenage years to mid-20s with the use of glucocorticoids and beyond the third decade with ventilator support and multidisciplinary care. However, Duchenne muscular dystrophy is associated with comorbidities and is a fatal disease. Glucocorticoids prolong ambulation, but their side effects are significant. Emerging investigational therapies have surfaced over the past decade and have rapidly been tested in clinical trials. Gene-specific strategies include nonsense readthrough, exon skipping, gene editing, utrophin modulation, and gene replacement. Other mechanisms include muscle regeneration, antioxidants, and antifibrosis and anti-inflammatory pathways. With potential therapies emerging, early diagnosis is needed to initiate treatment early enough to minimize morbidity and mortality. Newborn screening can be used to significantly improve early diagnosis, especially for gene-specific therapeutics.
بررسی میزان شیوع ژنهای مولد شیگاتوکسین (stx1, stx2) در سویههای اشریشیاکلی جدا شده از برههای نژاد سنگسری مبتلا به عفونت دستگاه گوارشی در منطقه سمنان با استفاده از تکنیک Multiplex – PCR

كچ ي هد :فده و هقباس وس ي ه اه ي رشا ي ش ي لکا ي ش دلوم ي سکوتاگ ي ن ب مارجا ي رام ي از يي ا ااب هک دنتسه ي ااج لوک داننام اي ت نوخ ر ي ز ي لومه موردنس و هدنه ي ت ي ک مروا ي ک طابترا ر ناسنا ر ش و دنا ي سکوتاگ ي ن ( اه stx1, stx2 اهم زا ) رات ي ن ا تدح لماوع ي ن وس ي ه م اه ي زا فده . دنشاب ا مااجنا اي ن اسررب هاعلاطم ي اش ي عو ا و رااشتن نژ ااه ي stx1 و stx2 ر وس ي ه اه ي E. coli هرب زا هدش ادج اه ي رسگنس اژن ي م نانمس رهش فارطا ر عقاو ي دشاب . شور و اوم ‌ :اه ط ي ي ک لاس راهب ر ههام هس هرو 3131 ادعت ، 361 ب هنومن ه داعقم بواس تروص ي هراب زا ااه ي ب و تشک ظاحل زا و هدش هتفرگ لاهسا موردنس هب لاتبم ي شو ي م ي ا يي زاسادج تهج ي رتکاب ي رشا ي اش ي لکا ي اب ه ناوانع ا لماع ي اج سررب تنوفع ي وس سپس و هدش ي ه اه ي E. coli زاسادج ي ب هدش ه شور هطاساو Multiplex-PCR تاهج ر ي با ي نژ اه ي stx سررب ي دندش . هتفاي ‌ :اه ادعت زا 361 روم هنومن سررب ي ، ادعت 13 وس ي ه E. coli ب ه ا لماع ناونع ي اج هرب ر لاهسا زااسادج ااه ي م زا . دندش ي نا 13 ادج ي ه ( ه زاو ادعت 42 وس )% ي ه ارا ي لقادح ي ک ي عاونا زا stx ب و دن وب ه ناونع STEC اشت ي ص م ر . دندش ه ا ي نا ا ي ن 34 وس ي ،ه ( جنپ 31 وس )% ي ه نژ لماح stx1 ، ( راهچ 8 وس )% ي ه نژ لماح stx2 ( هس ادعت و 6 )% وس ي ه راو و ره لماح ي هت stx دن وب . هجيتن ‌ :يريگ نژ روضح وانت اه ي stx1 و stx2 ح ر ي تاناو نب طابترا و ا اب اه ي ااج ب ي راام ي ا ر نااسنا ر اي نار ب ه بوخ ي ب . تسا هدشن ص شم ه ل ي ل لااب فرصم ي ب و دنفسوگ تشوگ ه راسگنس اژن نادنفسوگ شرورپ صوصخ ي ر وس روضح و نانمس فارطا هقطنم ي ه اه ي STEC هرب ر اه ي م ب لات م هاب لاهاسا موردنس هب اي ناز 42 هانومن ر % ااه ي ما عوفدم اه ي سررب ،هعلاطم روم ي ق ي ق عماج و رت ي ا ر ي ن اسانش تهج هطبار يي ق ي ق م رت ي ناز واس راشتنا ي ه ااه ي ش دلوم ي سکوتاگ ي ن ما ر اه ي قوف پ و لرتنک ،رکذلا ي گش ي ر ي قتسم راشتنا زا ي غ و ي قتسمر ي ا ي ن اب کرتشم لماع ي ن هرطا م و ما و ناسنا مب ي ز ن روم ي زا م ي دشاب . هژاو ‌ :يديلک ياه رشا ي ش ي لکا ي ش ي سکوتاگ ي نژ ي ،ک ش ي سکوتاگ ي ن 3 ، ش ي سکوتاگ ي ني ، دنفسوگ لاهسا ، نانمس
Driver Profiling Using Realistic Racing Games

All humans operating vehicles with several in-puts(steering wheel, pedals, gears etc.) do so in a unique way. We attempt to identify drivers based on this characteristic driving profile. Users were made to playa realistic 3D driving simulation, StuntRally. Their keypress events were logged. These logs were used to train and test different classifiers such as Support Vector Machine(SVM), K Nearest Neighbour(KNN) and Naive Bayes(NB). The SVM performed best with an average testing accuracy of 80 %.
Significance of Accuracy in Vowel Region Detection for Robust Language Identification

In this study, a robust language identification (LID) system is investigated with vowel region detection scheme incorporated at the front-end. The background noise is known to severely reduce language identification performance. In this work, Mel-frequency cepstral features extracted from the vowel regions instead of voiced speech are utilized for language identification system modeling. Experimentation is done using different vowel region detection algorithms on deep neural networks (DNN) and deep neural networks with attention (DNN-WA) based LID systems on IIITH Indian language dataset. Experimental results show that the accurate vowel region detection mechanism at the front-end of a LID system improved the performance in noisy environment.
A Framework for Adaptive Predictive Control System Based on Zone Control

In view of the degradation of predictive control performance caused by model mismatch, a multi-variable adaptive predictive control system framework which is composed of zone model predictive control (MPC), identification module and performance monitoring module, is presented. The proposed framework synthesizes the traditional control mode and the test mode to construct a unified form, which is convenient to implement with the MPC software packages. Traditional setpoint control is switched to zone control to ensure that the process constraints remain satisfied in testing, while multi-variable test signals are introduced to guarantee the sufficient excitation of the plant. In addition, in order to maximize the signal-to-noise ratio, an adaptive method of determining the amplitude of test signals is proposed. All the online open-loop identification methods are suitable for this framework, as the testing is treated as “open-loop,” which solves the problem of the correlation between input signals and noises in the closed-loop identification. These characteristics of the proposed framework are illustrated via a simulation.
Docker Container Deployment in Fog Computing Infrastructures

The transition from virtual machine-based infrastructures to container-based ones brings the promise of swift and efficient software deployment in large-scale computing infrastructures. However, in fog computing environments which are often made of very small computers such as Raspberry PIs, deploying even a very simple Docker container may take multiple minutes. We demonstrate that Docker makes inefficient usage of the available hardware resources, essentially using different hardware subsystems (network bandwidth, CPU, disk I/O) sequentially rather than simultaneously. We therefore propose three optimizations which, once combined, reduce container deployment times by a factor up to 4. These optimizations also speed up deployment time by about 30% in datacenter-grade servers.
New Polynomial Based Bit-Level Serial GF(2m) Multiplier for RS(15,11) 4-bit Codec Optimization

Reed Solomon Codec has been optimized by applying a new bit-level serial multiplier in the computation process of RS(15,11) 4-bit. The new multiplier took advantage of partial decoding process with fewer delay, and hence able to proceed in higher cycle rate. The RS Codec involves dominant multiplications which have been replaced by Fully Serial In Parallel Out (FSIPO) multiplier and implemented in Xilinx and Altium FPGA Board. The experiment results in throughput improvement of 11% and time efficiency of 23% in addition to automatic optimization by the synthesis tools due to the existence of constant variables in polynomial multiplications. This paper confirms that the most optimal RS Codec can be achieved by selecting the best configuration of GF arithmetic operators, each of which does not necessarily the best variant. A new perspective of GF application performance evaluation has been endorsed by the results reported in this paper.
Utilizing Blockchain Technology in Industrial Manufacturing with the help of Network Simulation

The fourth Industrial Revolution is finding its way into modern manufacturing sites. Assets with a certain degree of implemented communication technology will be enabled to interconnect and cooperate with practically every other entity via the Industrial Internet. An extreme amount of data and information will be exchanged all the time. Machines will be empowered to make crucial decisions autonomously influencing whole production processes. Erroneous, illegitimate or tampered data will lead to incorrect decisions and will be posing a huge threat to future strong cross-linked added value networks. An approach to tackle this issue comes from a technology called distributed ledger technology with its most known variant the “blockchain”. Certain properties of blockchain technology are showing promising enhancements for industrial networks primarily in order to guarantee digital trust. In this paper, issues like the ability to scale and the adaption onto the requirements of industrial networks are investigated. It turns out that simulation approaches must be taken into consideration, and a first step for an implementation is presented.
Efficacy of a Covalent ERK1/2 Inhibitor, CC-90003, in KRAS-Mutant Cancer Models Reveals Novel Mechanisms of Response and Resistance

As a critical signaling node, ERK1/2 are attractive drug targets, particularly in tumors driven by activation of the MAPK pathway. Utility of targeting the MAPK pathway has been demonstrated by clinical responses to inhibitors of MEK1/2 or RAF kinases in some mutant BRAF-activated malignancies. Unlike tumors with mutations in BRAF, those with mutations in KRAS (>30% of all cancers and >90% of certain cancer types) are generally not responsive to inhibitors of MEK1/2 or RAF. Here, a covalent ERK1/2 inhibitor, CC-90003, was characterized and shown to be active in preclinical models of KRAS-mutant tumors. A unique occupancy assay was used to understand the mechanism of resistance in a KRAS-mutant patient-derived xenograft (PDX) model of colorectal cancer. Finally, combination of CC-90003 with docetaxel achieved full tumor regression and prevented tumor regrowth after cessation of treatment in a PDX model of lung cancer. This effect corresponded to changes in a stemness gene network, revealing a potential effect on tumor stem cell reprograming. Implications: Here, a covalent ERK1/2 inhibitor (CC-90003) is demonstrated to have preclinical efficacy in models of KRAS-mutant tumors, which present a therapeutic challenge for currently available therapies.
Optimal Offloading in Fog Computing Systems With Non-Orthogonal Multiple Access

Fog computing has recently become a promising method to meet the increasing computation demands from mobile applications in the Internet of Things (IoT). In fog computing, the computation tasks of an IoT device can be offloaded to fog nodes. Due to the limited computation capacity of a fog node, the IoT device may try to offload its tasks to multiple fog nodes. In this paper, to improve the offloading efficiency, downlink non-orthogonal multiple access is applied in fog computing systems such that the IoT device can perform simultaneous offloading to multiple fog nodes. Then, to maximize the long-term average system utility, a task and power allocation problem for computation offloading is formulated subject to task delay and energy cost constraints. By the Lyapunov optimization method, the original problem is transformed to an online optimization problem in each time slot, which is non-convex. Accordingly, we propose an algorithm to solve the non-convex online optimization problem with polynomial complexity.
Methylation of imprinted IGF2 regions is associated with total, visceral, and hepatic adiposity in postmenopausal women

ABSTRACT Excess body fat, especially intra-abdominal fat, is a leading risk factor for metabolic diseases. Differentially methylated regions (DMRs) of two imprinted genes, insulin-like growth factor 2 (IGF2) and H19, have been associated with obesity due to their important roles in regulating body composition, but have not been examined in relation to intra-abdominal fat depots. Total body fat from whole-body dual energy X-ray absorptiometry and visceral and liver fat contents from abdominal magnetic resonance imaging in 48 healthy women aged 60–65 years (of White or Japanese ancestry) were each regressed on circulating leukocyte DNA methylation levels of IGF2 (at DMR0, DMR2a, and DMR2b) and H19 (at CTCF3) as assessed by pyrosequencing, while adjusting for age and race/ethnicity. Total fat mass was inversely associated with methylation levels of IGF2 DMR2b (P = 0.016). Total fat-adjusted visceral fat area (P = 0.062) and percent visceral fat measured at L4-L5 (P = 0.045) were associated with higher methylation levels of IGF2 DMR2b. Both total fat-adjusted percent liver fat (P = 0.039) and the presence of fatty liver (P = 0.015) were positively associated with IGF2 DMR2a methylation. Methylation levels of H19 CTCF3 were not associated with overall or intra/abdominal adiposity. The findings indicate that methylation levels of IGF2 DMR regions in leukocytes are associated with total body fat and with fat distribution in the viscera and liver independently of total adiposity.
Robust Dynamic Sliding Mode Control of a Deployable Cable Driven Robot

Despite of bing intensively developed, cable driven parallel manipulators are not yet vastly used due to their requirements for accurate assembly and installation. The main goal of this paper is to propose a suitable control method by which the robot could be suitably controlled without the requirement for undergoing any accurate calibration process. Here this robot is called deployable cable driven manipulator, in which the positions of the cable attachment points are not accurately known. This uncertainty in measurements will affect many parameters in the kinematic model especially the Jacobian matrix which is used as a force distributer in the Cartesian-space control strategies. In this paper in order to overcome this problem, a robust dynamic sliding mode controller is proposed. Then robust stability of the closed-loop system is analyzed through the Lyapunov direct method and by accordingly appropriate controller gain selection is performed. In order to illustrate the performance of the proposed controller, the robot is simulated in ADAMS software and it is shown that a suitable controller performance could be achieved.
Onchodermatitis: Where Are We Now?

Onchocerciasis causes debilitating pruritus and rashes as well as visual impairment and blindness. Prior to control measures, eye disease was particularly prominent in savanna areas of sub-Saharan Africa whilst skin disease was more common across rainforest regions of tropical Africa. Mass drug distribution with ivermectin is changing the global scene of onchocerciasis. There has been successful progressive elimination in Central and Southern American countries and the World Health Organization has set a target for elimination in Africa of 2025. This literature review was conducted to examine progress regarding onchocercal skin disease. PubMed searches were performed using keywords ‘onchocerciasis’, ‘onchodermatitis’ and ‘onchocercal skin disease’ over the past eight years. Articles in English, or with an English abstract, were assessed for relevance, including any pertinent references within the articles. Recent progress in awareness of, understanding and treatment of onchocercal skin disease is reviewed with particular emphasis on publications within the past five years. The global burden of onchodermatitis is progressively reducing and is no longer seen in children in many formerly endemic foci.
A 2-MHz BW 82-dB DR Continuous-Time Delta–Sigma Modulator With a Capacitor-Based Voltage DAC for ELD Compensation

In this paper, we present a third-order nine-level continuous-time delta–sigma modulator, in which a capacitor-based voltage digital-to-analog converter is used to compensate for excess loop delay of up to half a clock period, with margins of ±30%. To evaluate its effectiveness, the prototype is implemented in 65-nm CMOS technology with an active area of 0.516 mm2. The experimental results show a dynamic range (DR) of 82 dB, a signal-to-noise ratio of 75.8 dB, a signal-to-noise-and-distortion ratio of 72.1 dB, and a spurious-free DR of 78.8 dB at a sampling frequency of 128 MHz and a bandwidth of 2 MHz. The total power consumption is 3.8 mW from a 1.2-V supply.
Adapting Deep Features for Scene Recognition utilizing Places Database

The undertaking is endeavour to assign energy of tactile systems for recognising scene. This investigations makes utilization of MIT Indoor 67 datasets by expect to perceive how the CNN coordinate to present business principles of acknowledgment. Methods, for example, tricking the CNN helped support execution by decreasing disarray between the most confounded sets of classes. Furthermore, the task analyzes the distinction in properties between indoor-driven versus outside driven datasets, which are in charge of the stamped contrast in execution on comparable CNN structures.
The diagnostic value of cell blocks in liquid‐based cytology of bronchial aspiration and bronchial brushing materials: Methodological issues

We were interested to read the paper by Sadullahoğlu C and colleagues published in the April 2018 issue of the Cytopathology. The authors aimed to identify the diagnostic value of conventional smear, Liquid-based cytology (LBC) and cell block (CB) methods in bronchial cytological specimens. The cytological diagnoses were compared with the final diagnosis or the endoscopic findings of 114 patients with neoplasia. Based on their results, CB led to a 10.1% increase in the diagnostic sensitivity for bronchial aspiration (BA) specimens, while no significant increase was seen in bronchial brush specimens. They concluded that adding cell block to CB and LBC seemed to contribute the cytological diagnosis in BA materials significantly. This article is protected by copyright. All rights reserved.