Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Grey Wolf Optimization for Solving Combinatorial Problems: Job Shop and Flexible Job Shop Scheduling Cases

Grey wolf optimization (GWO) algorithm is a new population-oriented intelligence algorithm, which is originally proposed to solve continuous optimization problems inspired from the social hierarchy and hunting behaviors of grey wolves. It has been proved that GWO can provide competitive results compared with some well-known meta-heuristics. This paper aims to employ the GWO to deal with two combinatorial optimization problems in the manufacturing field: job shop and flexible job shop scheduling cases. The effectiveness of GWO algorithm on the two problems can give an idea about its possible application on solving other scheduling problems. For the discrete characteristics of the scheduling solutions, we developed a kind of discrete GWO algorithm with the objective of minimizing the maximum completion time (makespan). In the proposed algorithm, searching operator is designed based on the crossover operation to maintain the algorithm work directly in a discrete domain. Then an adaptive mutation method is introduced to keep the population diversity and avoid premature convergence. In addition, a variable neighborhood search method is embedded to further enhance the exploration. To evaluate the effectiveness, the discrete GWO algorithm is compared with other published algorithms in the literature for the two scheduling cases. Experimental results demonstrate that our algorithm outperforms other algorithms for the scheduling problems under study.
The effect of coppice management on the structure, tree growth and soil nutrients in temperate Turkey

Coppicing was widespread throughout Europe for many centuries but was largely abandoned in the second half of the 19 th century. Currently, there has been a renewed interest in coppicing for biomass production and nature conservation. We studied differences in soil chemistry and tree growth between active and abandoned coppices to highlight the impacts of coppice restoration on soil fertility and tree. Stand structure, collected soil samples and tree cores were compared on 46 research plots in temperate Turkey. The plots were set as actively managed and abandoned coppice stand. In our study no effect of coppicing on growth rate was confirmed. Active coppice stands had lower content of Ca, K, N and C:N and higher soil acidification than abandoned coppices. The tree growth rate was significantly higher on more nutrient-rich soils. Coppice restoration may not result in increased biomass production in long-term periods due to a negative effect on soil fertility.
The normalized radial basis function neural network

Presents a neural network called the normalized radial basis function (NRBF) neural network. The NRBF integrates techniques from two similar neural networks: the general regression neural network (GRNN) and the radial basis function (RBF) neural network. The NRBF is identical to the standard radial basis function (RBF) network except the hidden layer outputs are normalized before being passed through the output layer. The normalization of the hidden layer weights is shown to improve the extrapolation performance of the conventional RBF network. We have reason to believe that under normal circumstances the NRBF outperforms the RBF and the GRNN.
KINEMATICS OF THORAX AND PELVIS DURING MAXIMAL ACCELERATED SPRINTING

Changes in thorax and pelvis movements during acceleration phase of maximal sprinting, which relate to acceleration ability, are still unknown. This study aimed to clarify the changes in thorax and pelvis movements during maximal accelerated sprinting and its relation to better acceleration ability. Twelve sprinters performed a 60-m sprint, during which 3D kinematics of the sprinters were obtained. The same patterns of motions were maintained for thorax and pelvis respectively throughout the entire acceleration phase, although phase profiles of relative movements between thorax and pelvis in three planes differed. Moreover, results indicated that effective acceleration is characterised by suppressed trunk bend, delayed trunk rotation, and forward tilted pelvis in the middle acceleration section and suppressed trunk bend in the final acceleration section.
Loss of 5hmC identifies a new type of aberrant DNA hypermethylation in glioma

Aberrant DNA hypermethylation is a hallmark of cancer although the underlying molecular mechanisms are still poorly understood. To study the possible role of 5-hydroxymethylcytosine (5hmC) in this process we analyzed the global and locus-specific genome-wide levels of 5hmC and 5-methylcytosine (5mC) in human primary samples from 12 non-tumoral brains and 53 gliomas. We found that the levels of 5hmC identified in non-tumoral samples were significantly reduced in gliomas. Strikingly, hypo-hydroxymethylation at 4627 (9.3%) CpG sites was associated with aberrant DNA hypermethylation and was strongly enriched in CpG island shores. The DNA regions containing these CpG sites were enriched in H3K4me2 and presented a different genuine chromatin signature to that characteristic of the genes classically aberrantly hypermethylated in cancer. As this 5mC gain is inversely correlated with loss of 5hmC and has not been identified with classical sodium bisulfite-based technologies, we conclude that our data identifies a novel 5hmC-dependent type of aberrant DNA hypermethylation in glioma.
Risky behaviors of taxi drivers in Bandar Abbas, Iran

Background and aim It has been revealed that taxi drivers break more traffic rules than ordinary drivers. Such risky behaviors include stopping at prohibited areas and sudden change of direction. The present study aimed to determine the Risky Behaviors of Taxi Drivers in Bandar Abbas, Iran Methods In this cross-sectional study, 184 taxi drivers were randomly selected from eight taxi stations located at different parts of Bandar Abbas city in 2016. Taxi drivers’ risky behaviors were evaluated via a 20-item questionnaire. Data were analyzed by SPSS version 19, using descriptive statistics and independent-samples t-test. The p-values less than 0.05 were considered as statistically significant. Results The mean age of the drivers was 45.1 (±11.1) years. The mean of their occupational experience was 18.7 (±10.8) years. The risky behaviors which showed the highest frequency were respectively, failure to use signal-lights, driving too close to the cars in front, refusing to drive within the lanes and erratic lane changing. The lowest frequency belonged to running a red light, ignoring ‘no entry’ signs and taking illegal U-turns. Risky driving behaviors were shown to be significantly more prevalent among drivers with previous experience of crashes or tickets than drivers with no such experiences (p<0.01). Conclusion Increasing the role of police supervision for the strict implementation of driving laws, and modification of the drivers’ behavior and implementation of periodic training programs on drivers’ safety issues can be considered for reducing taxi drivers’ unsafe behaviors.
Emerging role of long non-coding RNAs in cisplatin resistance

Cisplatin (CDDP) is one of the most commonly used chemotherapy drugs for the treatment of various cancers. Although platinum-based therapies are highly efficacious against rapidly proliferating malignant tumors, the development of CDDP resistance results in significant relapse as well as decreased overall survival rates, which is a significant obstacle in CDDP-based cancer therapy. Long non-coding RNAs (lncRNAs) are involved in cancer development and progression by the regulation of processes related to chromatin remodeling, transcription, and posttranscriptional processing. Emerging evidence has recently highlighted the roles of lncRNAs in the development of CDDP resistance. In this review, we discuss the roles and mechanisms of lncRNAs in CDDP chemoresistance, including changes in cellular uptake or efflux of a drug, intracellular detoxification, DNA repair, apoptosis, autophagy, cell stemness, and the related signaling pathways, aiming to provide potential lncRNA-targeted strategies for overcoming drug resistance in cancer therapy.
A Linguistically-Informed Fusion Approach for Multimodal Depression Detection

Automated depression detection is inherently a multimodal problem. Therefore, it is critical that researchers investigate fusion techniques for multimodal design. This paper presents the first-ever comprehensive study of fusion techniques for depression detection. In addition, we present novel linguistically-motivated fusion techniques, which we find outperform existing approaches.
Application-Driven End-to-End Slicing: When Wireless Network Virtualization Orchestrates With NFV-Based Mobile Edge Computing

Recently, to adapt to the various quality-of-service (QoS) requirements of emerging applications, application-driven network slicing has attracted intensive interests. In this paper, we apply the idea of software-defined wireless network virtualization (WiNV) to WiFi networks and design and demonstrate a novel network system, namely, ADE2WiNFV. The proposed system can orchestrate software-defined WiNV with network-function-virtualization-based mobile edge computing (MEC) to realize application-driven end-to-end (E2E) slicing over heterogeneous wireline/wireless networks. Our experimental demonstrations verify that ADE2WiNFV can realize application-aware E2E slices on demand, each of which contains not only guaranteed E2E bandwidth resources (i.e., in the forms of virtual links, virtual switches, and virtual access points) but also isolated IT resources (i.e., in the form of virtual network functions) to carry specific applications with QoS guarantees.
RVNoC: A Framework for Generating RISC-V NoC-Based MPSoC

With the increase in the number of cores embedded on a chip; The main challenge for Multiprocessor System-on-Chip (MPSoC) platforms is the interconnection between that massive number of cores. Networks-on-Chip (NoC) was introduced to solve that challenge, by providing a scalable and modular solution for communication between the cores. In this paper, we introduce a configurable MPSoC framework called RVNoC that generates synthesizable RTL that can be used in both ASIC and FPGA implementations. The proposed framework is based on the open source RISC-V Instruction Set Architecture (ISA) and an open source configurable flit-based router for interconnection between cores, with a core network interface of our design to connect each core with its designated router. A benchmarking environment is developed to evaluate variant parameters of the generated MPSoC. Synthesis of a single building block containing a single core without any peripherals, a router, and a core network interface, using 45nm technology, shows an area of 102.34 kilo Gate Equivalents (kGE), a maximum frequency of 250 MHz, and a 9.9 μW/MHz power consumption.
End-to-end Speech Recognition Using Lattice-free MMI

We present our work on end-to-end training of acoustic models using the lattice-free maximum mutual information (LF-MMI) objective function in the context of hidden Markov models. By end-to-end training, we mean ﬂat-start training of a single DNN in one stage without using any previously trained models, forced alignments, or building state-tying decision trees. We use full biphones to enable context-dependent modeling without trees, and show that our end-to-end LF-MMI approach can achieve comparable results to regular LF-MMI on well-known large vocabulary tasks. We also compare with other end-to-end methods such as CTC in character-based and lexicon-free settings and show 5 to 25 percent relative reduction in word error rates on different large vocabulary tasks while using signiﬁ-cantly smaller models.
Tubular and Spherical SiO2 Obtained by Sol Gel Method for Lipase Immobilization and Enzymatic Activity

A wide range of hybrid biomaterials has been designed in order to sustain bioremediation processes by associating sol-gel SiO2 matrices with various biologically active compounds (enzymes, antibodies). SiO2 is a widespread, chemically stable and non-toxic material; thus, the immobilization of enzymes on silica may lead to improving the efficiency of biocatalysts in terms of endurance and economic costs. Our present work explores the potential of different hybrid morphologies, based on hollow tubes and solid spheres of amorphous SiO2, for enzyme immobilization and the development of competitive biocatalysts. The synthesis protocol and structural characterization of spherical and tubular SiO2 obtained by the sol gel method were fully investigated in connection with the subsequent immobilization of lipase from Rhizopus orizae. The immobilization is conducted at pH 6, lower than the isoelectric point of lipase and higher than the isoelectric point of silica, which is meant to sustain the physical interactions of the enzyme with the SiO2 matrix. The morphological, textural and surface properties of spherical and tubular SiO2 were investigated by SEM, nitrogen sorption, and electrokinetic potential measurements, while the formation and characterization of hybrid organic-inorganic complexes were studied by UV-VIS, FTIR-ATR and fluorescence spectroscopy. The highest degree of enzyme immobilization (as depicted from total organic carbon) was achieved for tubular morphology and the hydrolysis of p-nitrophenyl acetate was used as an enzymatic model reaction conducted in the presence of hybrid lipase–SiO2 complex.
Tachypleus tridentatus Lectin Enhances Oncolytic Vaccinia Virus Replication to Suppress In Vivo Hepatocellular Carcinoma Growth

Lectins play diverse roles in physiological processes as biological recognition molecules. In this report, a gene encoding Tachypleus tridentatus Lectin (TTL) was inserted into an oncolytic vaccinia virus (oncoVV) vector to form oncoVV-TTL, which showed significant antitumor activity in a hepatocellular carcinoma mouse model. Furthermore, TTL enhanced oncoVV replication through suppressing antiviral factors expression such as interferon-inducible protein 16 (IFI16), mitochondrial antiviral signaling protein (MAVS) and interferon-beta (IFN-β). Further investigations revealed that oncoVV-TTL replication was highly dependent on ERK activity. This study might provide insights into a novel way of the utilization of TTL in oncolytic viral therapies.
Title Characterization of early and terminal complement proteins associated with polymorphonuclear leukocytes in vitro and in vivo after spinal cord injury

Background: The complement system has been suggested to affect injury or disease of the central nervous system (CNS) by regulating numerous physiological events and pathways. The activation of complement following traumatic CNS injury can also result in the formation and deposition of C5b-9 membrane attack complex (C5b-9/MAC), causing cell lysis or sublytic effects on vital CNS cells. Although complement proteins derived from serum/blood-brain barrier breakdown can contribute to injury or disease, infiltrating immune cells may represent an important local source of complement after injury. As the first immune cells to infiltrate the CNS within hours post-injury, polymorphonuclear leukocytes (PMNs) may affect injury through mechanisms associated with complement-mediated events. However, the expression/association of both early and terminal complement proteins by PMNs has not been fully characterized in vitro, and has not observed previously in vivo after traumatic spinal cord injury (SCI). Method: We investigated the expression of complement mRNAs using rt-PCR and the presence of complement proteins associated with PMNs using immunofluroescence and quantitative flow cytometry. Results: Stimulated or unstimulated PMNs expressed mRNAs encoding for C1q, C3, and C4, but not C5, C6, C7 or C9 in culture. Complement protein C1q or C3 was also detected in less than 30% of cultured PMNs. In contrast, over 70% of PMNs that infiltrated the injured spinal cord were associated with C1q, C3, C7 and C5b-9/MAC 3 days post-SCI. The localization/association of C7 or C5b-9/MAC with infiltrating PMNs in the injured spinal cord suggests the incorporation or internalization of C7 or C5b-9/MAC bound cellular debris by infiltrating PMNs because C7 and C5b-9/MAC were mostly localized to granular vesicles within PMNs at the spinal cord epicenter region. Furthermore, PMN presence in the injured spinal cord was observed for many weeks post-SCI, suggesting that this infiltrating cell population could chronically affect complement-mediated events and SCI pathogenesis after trauma. Conclusion: Data presented here provide the first characterization of early and terminal complement proteins associated with PMNs in vitro and in vivo after SCI. Data also suggest a role for PMNs in the local internalization or deliverance of complement and complement activation in the post-SCI environment. Published: 25 June 2008 Journal of Neuroinflammation 2008, 5:26 doi:10.1186/1742-2094-5-26 Received: 28 January 2008 Accepted: 25 June 2008 This article is available from: http://www.jneuroinflammation. com/content/5/1/26 © 2008 Nguyen et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
IR-BASED SATELLITE PRODUCTS FOR THE MONITORING OF ATMOSPHERIC WATER VAPOR OVER THE BLACK SEA

– IR-BASED SATELLITE PRODUCTS FOR THE MONITORING OF ATMOSPHERIC WATER VAPOR OVER THE BLACK SEA. The amount of precipitable water (TPW) in the atmospheric column is one of the important information used weather forecasting. Some of the studies involving the use of TPW relate to issues like lightning warning system in airports, tornadic events, data assimilation in numerical weather prediction models for short-range forecast, TPW associated with intense rain episodes. Most of the available studies on TPW focus on properties and products at global scale, with the drawback that regional characteristics – due to local processes acting as modulating factors may be lost. For the Black Sea area, studies on the climatological features of atmospheric moisture are available from sparse or not readily available observational databases or from global reanalysis. These studies show that, although a basin of relatively small dimensions, the Black Sea presents features that may significantly impact on the atmospheric circulation and its general characteristics. Satellite observations provide new opportunities for extending the knowledge on this area and for monitoring atmospheric properties at various scales. In particular, observations in infrared (IR) spectrum are suitable for studies on smallscale basins, due to the finer spatial sampling and reliable information in the coastal areas. As a first step toward the characterization of atmospheric moisture over the Black Sea from satellite-based information, we investigate three datasets of IR-based products which contain information on the total amount of moisture and on its vertical distribution, available in the area of interest. The aim is to provide a comparison of these data with regard to main climatological features of moisture in this area and to highlight particular strengths and limits of each of them, which may be helpful in the choice of the most suitable dataset for a certain application.
Regular walking breaks prevent the decline in cerebral blood flow associated with prolonged sitting.

Decreased cerebrovascular blood flow and function are associated with lower cognitive functioning and increased risk of neurodegenerative diseases. Prolonged sitting impairs peripheral blood flow and function, but its effects on the cerebrovasculature are unknown. This study explored the effect of uninterrupted sitting and breaking up sitting time on cerebrovascular blood flow and function of healthy desk workers. Fifteen participants (10 male, 35.8 ± 10.2 yr, body mass index: 25.5 ± 3.2 kg/m2) completed, on separate days, three 4-h conditions in a randomized order: 1) uninterrupted sitting (SIT), 2) sitting with 2-min light-intensity walking breaks every 30 min (2WALK), or 3) sitting with 8-min light-intensity walking breaks every 2 h (8WALK). At baseline and 4 h, middle cerebral artery blood flow velocity (MCAv) and CO2 reactivity (CVR) of the MCA and carotid artery were measured using transcranial Doppler (TCD) and duplex ultrasound, respectively. Cerebral autoregulation (CA) was assessed with TCD using a squat-stand protocol and analyzed to generate values of gain and phase in the very low, low, and high frequencies. There was a significant decline in SIT MCAv (-3.2 ± 1.2 cm/s) compared with 2WALK (0.6 ± 1.5 cm/s, P = 0.02) but not between SIT and 8WALK (-1.2 ± 1.0 cm/s, P = 0.14). For CA, the change in 2WALK very low frequency phase (4.47 ± 4.07 degrees) was significantly greater than SIT (-3.38 ± 2.82 degrees, P = 0.02). There was no significant change in MCA or carotid artery CVR ( P > 0.05). Results indicate that prolonged uninterrupted sitting in healthy desk workers reduces cerebral blood flow; however, this is offset when frequent short-duration walking breaks are incorporated. NEW & NOTEWORTHY Prolonged uninterrupted sitting in healthy desk workers reduces cerebral blood flow. However, this reduction in cerebral blood flow is offset when frequent short-duration walking breaks are incorporated into this sitting period. For those who engage in long periods of sedentary behavior, chronically breaking up these sitting periods with frequent active break strategies may have important implications for cerebrovascular health; however, further research should explore this hypothesis.
On-line model learning for adaptive GNSS ionospheric scintillation estimation and mitigation

One of the more challenging propagation conditions in Global Navigation Satellite Systems (GNSS), clearly affecting high-precision receivers and safety critical applications, is ionospheric scintillation. One of the main disadvantages of standard phase tracking architectures is the estimation vs mitigation tradeoff, that is, it is impossible to distinguish between the line-of-sight (LOS) phase contribution of interest and phase variations induced by the ionosphere. A possible solution is to consider a state-space formulation of the problem, where the scintillation amplitude and phase are estimated together with the LOS phase variations. The current Kalman filter-based techniques exploiting this idea consider an off-line scintillation model fitting, thus not suitable for real-life applications. In this contribution we propose an adaptive model learning strategy to be able to cope with time-varying unknown scintillation conditions. The performance of the new approach is shown using real ionospheric scintillation data recorded over Hanoi in 2015.