Miracle-dz/UniFAR-FTUs huggingface dataset:
Physiological and biochemical markers in the process of resistance and/or tolerance of heavy metals in the abandoned mining area of Sidi Kamber, Skikda, Algeria

Abstract This paper reports the biomonitoring of metallic pollution in the mine of Sidi Kamber Skikda town, to determine the resistance and/or tolerance to Zn, Pb, Cd and Cu in metalliferous plants. During the period of March–May, 2015, soil and plants samples were collected from three different stations in the study area. The total heavy metal fraction was determined by ICP/MS, whereas biochemical markers were determined by spectrophotometric techniques. The results obtained showed high levels of heavy metals in soil and plants compared to international standards. The translocation factor revealed that the studied plants can transfer and/or accumulate metals in their roots or their aerial parts as a function of characteristics of each metal, soil contents and physiological role in the plant. The contents of chlorophyll, proline, total sugars and total proteins are directly influenced by changes in bioavailable contents of heavy metals. It has been found that the plants studied and biomarkers are better suited for phytoremediation and biomonitoring of heavy metals pollution.
Total Flavonoids of Glycyrrhiza uralensis Alleviates Irinotecan-Induced Colitis via Modification of Gut Microbiota and Fecal Metabolism

Irinotecan (CPT-11)-induced gastrointestinal toxicity strongly limits its anticancer efficacy. Glycyrrhiza uralensis Fisch. , especially flavonoids, has strong anti-inflammatory and immunomodulatory activities. Herein, we investigate the protective effect of the total flavonoids of G. uralensis (TFGU) on CPT-11–induced colitis mice from the perspective of gut microbiota and fecal metabolism. The body weight and colon length of mice were measured. Our results showed that oral administration of TFGU significantly attenuated the loss of body weight and the shortening of colon length induced by CPT-11. The elevated disease activity index and histological score of colon as well as the up-regulated mRNA and protein levels of TNF-α, IL-1β, and IL-6 in the colonic tissue of CPT-11–treated mice were significantly decreased by TFGU. Meanwhile, TFGU restored the perturbed gut microbial structure and function in CPT-11–treated mice to near normal level. TFGU also effectively reversed the CPT-11–induced fecal metabolic disorders in mice, mainly call backing the hypoxanthine and uric acid in purine metabolism. Spearman’s correlation analysis further revealed that Lactobacillus abundance negatively correlated with fecal uric acid concentration, suggesting the pivotal role of gut microbiota in CPT-11–induced colitis. Since uric acid is a ligand of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, TFGU was further validated to inhibit the activation of NLRP3 inflammasome by CPT-11. Our findings suggest TFGU can correct the overall gut microbial dysbiosis and fecal metabolic disorders in the CPT-11–induced colitis mice, underscoring the potential of using dietary G. uralensis as a chemotherapeutic adjuvant.
Droplet-Based Microfluidic High Throughput Screening of Corynebacterium glutamicum for Efficient Heterologous Protein Production and Secretion

With emerging interests in heterologous production of proteins such as antibodies, growth factors, nanobodies, high-quality protein food ingredients, etc. the demand for efficient production hosts increases. Corynebacterium glutamicum is an attractive industrial host with great secretion capacity to produce therapeutics. It lacks extracellular protease and endotoxin activities and easily achieves high cell density. Therefore, this study focuses on improving protein production and secretion in C. glutamicum with the use of droplet-based microfluidic (DBM) high throughput screening. A library of C. glutamicum secreting β-glucosidase was generated using chemical mutagenesis coupled with DBM screening of 200,000 mutants in just 20 min. Among 100 recovered mutants, 16 mutants exhibited enhanced enzyme secretion capacity, 13 of which had unique mutation profiles. Whole-genome analysis showed that approximately 50–150 SNVs had occurred on the chromosome per mutant. Functional enrichment analysis of genes with non-synonymous mutations showed overrepresentation of genes involved in protein synthesis and secretion relevant biological processes, such as DNA and ribosome RNA synthesis, protein secretion and energy turnover. Two mutants JCMT1 and JCMT8 exhibited the highest secretion with a six and a fivefold increase in the β-glucosidase activity in the supernatant, respectively, relative to the reference strain JC0190. After plasmid curing, a new plasmid with the gene encoding α-amylase was cloned into these two mutants. The new strains SB024 and SB025 also exhibited a five and a sixfold increase in α-amylase activity in the supernatant, respectively, relative to the reference strain SB023. The results demonstrate how DBM screening can serve as a powerful development tool to improve cell factories for the production and secretion of heterologous proteins.
Do Infant Faces Maintain the Attention of Adults With High Avoidant Attachment?

We investigated whether adults have attentional bias toward infant faces, whether it is moderated by infant facial expression, and the predictive effect of the adult attachment state on it. One hundred unmarried nulliparous college students [50 men and 50 women; aged 17–24 years (M = 19.70, SD = 1.35)] were recruited. Each completed a self-report questionnaire—the Chinese version of the State Adult Attachment Measure (SAAM), and a dot-probe task with a stimulus presentation duration of 500 ms, which used 192 black-and-white photographs of 64 people (32 infants and 32 adults; each person displayed three expressions: happy, neutral, and sad) as the experimental stimuli. The results showed that, at the duration of 500 ms, individuals' attentional bias toward infant faces disappeared, regardless of the facial expression. However, when the interaction between avoidant attachment state and face was controlled, the attentional bias was significant again, and the avoidant attachment state negatively predicted individuals' attentional bias toward infant faces. This indicates that at the suprathreshold stage, there are individual differences in the attentional bias toward infant faces, and high avoidant attachment will weaken individuals' attentional bias toward infant faces. This study advances previous studies that focused only on individuals' attention to infant faces occurring at the early processing stage of attention. The results provide direction for interventions; specifically, changing the attachment state of avoidant individuals can affect their attention to infants, which may promote the establishment of parent–child relationships.
Experimental Evaluation of Orchestration Software for Virtual Network Functions

The adoption of Network Functions Virtualization (NFV) is considered as one of the enablers for a fully softwarized 5G architecture, that allows significantly higher flexibility for network service providers to instantiate services, conFigure and update them, as well as to truly realize multi-tenancy. The key enablers of the NFV technology lie in the evolution of virtualization technologies, such as the long established Virtual Machines, and the more recent paradigms of containers for micro-services, like docker and LXC. Such technologies allow the virtualization to span even to the wireless RAN, with fully softwarized base station architectures. Nevertheless, with the plethora of different virtualization technologies, several Virtual Infrastructure Managers (VIMs) and service orchestrators have emerged, each of them addressing different aspects for the provided services e.g. possible nomadic behaviour of the hosting computers, resource constrained devices hosting the services and services deployed for time critical services to name a few. In this work, we use a reference setup and experiment with some of the most widely adopted infrastructure managers, trying to experimentally derive and validate their differences under varying loads of traffic. Our results reveal the time needed for instantiating the same service function, for dockers, containers and Virtual Machines, for a different number of VNFs.
Effect of valence states of Ni and Mn on the structural and electrochemical properties of Li1.2NixMn0.8−xO2 cathode materials for lithium-ion batteries

Severe capacity fading and voltage decay of Li-rich layered oxides for lithium-ion batteries remain the major bottlenecks to commercialization. Herein, we studied the effect of valence states of Ni and Mn on the structure and electrochemical performances of Li1.2NixMn0. 8−xO2. The oxidation states of the transition-metal (TM) were evaluated by X-ray photoelectron spectra (XPS) and validated by cyclic voltammetry (CV). With increasing Mn3+ content, the Li2MnO3 component increases due to less Li loss. The phenomenon of capacity increase upon cycling has been observed owing to the gradual activation of Li2MnO3 caused by the existence of Mn3+. It is worth mentioning that Li1.2Ni0. 1Mn0.7O2 reaches the highest discharge capacity value of 231.5 mA h g−1 from the initial value of 76 mA h g−1 after 75 cycles and still keeps 100% of the capacity at 0.1C after 100 cycles. With the increase of Ni3+, Li/Ni mixing decreases because of its smaller size than Ni2+, the content of Li2MnO3 decreases as a result of the decrease of Li and Mn in the TM layers, and the discharge voltage increases on account of the higher reduction potential of Ni4+/Ni3+ compared with Ni4+/Ni2+ and Mn4+/Mn3+. Furthermore, Li1.2Ni0. 4Mn0.4O2 delivers a first capacity value of 192.5 mA h g−1 and operating voltage of 3.89 V at 0.1C, and capacity retention of 92.13% and a voltage drop of 0.25 V after 100 cycles, which indicates that the stability of capacity and voltage is improved by a large margin with increasing Ni3+.
Computer-Aided Laccase Engineering: Toward Biological Oxidation of Arylamines

Oxidation of arylamines, such as aniline, is of high industrial interest, and laccases have been proposed as biocatalysts to replace harsh chemical oxidants. However, the reaction is hampered by the redox potential of the substrate at acid pH, and enzyme engineering is required to improve the oxidation. In this work, instead of trying to improve the redox potential of the enzyme, we aim toward the (transient) substrate’s potential and propose this as a more reliable strategy. We have successfully combined a computational approach with experimental validation to rationally design an improved biocatalyst. The in silico protocol combines classical and quantum mechanics to deliver atomic and electronic level detail on the two main processes involved: substrate binding and electron transfer. After mutant expression and comparison to the parent type, kinetic results show that the protocol accurately predicts aniline’s improved oxidation (2-fold kcat increase) in the engineered variant for biocatalyzed polyanili.
Do not Waste the Waste: Packetized Rateless Algebraic Consistency for IEEE 802.11 Networks

Future communication systems will require low latencies, especially for the small packets used in control applications. In WiFi systems, the main contributors to delays are retransmissions and congestions. Many of the transmitted packets are received with errors at the destination, and they are dropped at the MAC layer. Even if the number of errors is small the packets are discarded. Dropped partial packets are retransmitted, increasing the delays of the system because retransmissions involve new access to a shared medium. We show in our measurement campaign of IEEE 802.11 networks that between 5% and over 50% of the received packets, depending on the Modulation and Coding Scheme (MCS), have errors. However, only a few bits are erroneous (between 2% and 10%). Therefore, we show that a partial packet recovery technique based on network coding can make use of 55% more packets that otherwise would be dropped, which reduces the number of retransmissions and delays. Furthermore, if the length of the packets is short (between 50 and 250 Bytes) the computational overhead is low, which makes the implementation feasible, in such networks, for the short packets typical of applications of control of cyber-physical systems.
Time Minimization in Downlink Hybrid NOMA Wireless Powered Communication Networks

In this paper, we investigate the time minimization in the downlink (DL) wireless powered transmission network (WPCN) consisting of one base station (BS) and two energy harvesting (EH) users. The hybrid non orthogonal multiple access (H-NOMA) and hybrid EH scheme are adopted, in which each user can harvest energy from both the dedicated energy signal and the information signal for the other user. We aim to minimize the total time consumption under the data rate and energy consumption constraints. To solve the formulated non-convex problem, we propose a two-layer iterative algorithm. The problem in the inner layer is transformed to convex and the problem in the outer layer focused on the power allocation coefficient can be solved by binary search. Simulation results show that H-NOMA can achieve the best performance compared with time-division multiple access (TDMA) and NOMA, and NOMA also outperforms TDMA under the zero circuit power and little decoding power.
Cell Range Expansion in Backhaul Capacity Limited Massive MIMO HetNets

In this paper, we consider the small cell range expansion problem in massive multiple-input multiple-output (MIMO) heterogeneous networks (HetNets) with limited backhaul capacity, and derive the close-form formulas to calculate the range expansion bias (REB) of equal uplink received signal strengths (RSSs) boundary (EUB). In order to reduce the effect of severe downlink intercell interference in the expanded regions (ERs) of small cell, we propose a downlink precoding scheme based on the estimated channel state information (CSI). Simulation results verify the relationships among different small cell coverage boundaries, and demonstrate the benefits of the proposed downlink precoding scheme in maximizing the overall sum rate and improving the performance of MIMO HetNets.
LDPC Decoders using Non-Uniform Quantizers and Associative Check Node Operations

In this paper, we present a class of associative check node operations for LDPC decoders operating on non-uniformly quantized channel outputs over a binary-input additive white Gaussian noise channel (BIAWGNC). The proposed quantizer has thresholds that depend on the noise variance and can be easily calculated using binary search. A relatively small collection of check node operations is proposed where each operation can be described using a short list of integers. Simulation results using rate-1/2 and 2/3 DVB-S2 codes indicate that the proposed decoder under 4-bit quantization can come close to floating-point sum-product decoder error performance in the waterfall region to within 0.4 dB and 0.1 dB for the rate-1/2 and 2/3 codes, respectively. Moreover, tests with short LDPC codes indicate that the proposed 4-bit decoders may approach or even surpass floating-point error performance at high signal-to-noise ratios.
A Survey on Applying Automated Recognition of Touchscreen Stroke Gestures to Children's Input

Gesture recognition algorithms help designers create intelligent user interfaces for a number of application areas. However, these recognition algorithms are usually designed to recognize the gestures of adults, not children, and as such they generally do not perform as well for children as adults. Recognition of younger children’s gestures is particularly poor when compared to recognition of older children’s and adults’ gestures. Researchers have begun to examine the aspects of children’s gesture articulation patterns that make recognition difficult. This paper extends the initial work examining child-specific recognition approaches by considering general-purpose approaches and how they might apply to the problem of recognizing children’s touchscreen gestures. This paper presents a survey of existing recognition and analysis techniques for gestures of both adults and children from a human-centered perspective, highlighting ways in which improved recognition can lead to a better experience for children using touchscreen gestures in a variety of contexts.
Enriching Indoor Localization Fingerprint using A Single AC-GAN

For WiFi indoor localization, collecting the data to construct the fingerprint dataset is a time-consuming and laborious job. In this paper, we propose to alleviate the time-intensive data-labeling by generating artificial fingerprint using a single AC-GAN. Compared to the existing multi-GAN approaches, we show that the use of a single AC-GAN could achieve the improved accuracy in localization, which is validated by extensive experiments. We also discuss its potential limit.
Graph Attention Network-based DRL for Network Slicing Management in Dense Cellular Networks

Network slicing (NS) devotes to provisioning various services with distinct requirements over the same physical communication infrastructure. Considering a dense cellular network scenario that contains several NS over multiple base stations (BSs), it remains challenging to design a proper resource management strategy in real time, so as to cope with frequent BS handover and meet distinct service requirements. In this paper, we propose to formulate this challenge as a multiagent reinforcement learning (MARL) problem and leverage graph attention network (GAT) to strengthen the cooperation between agents. Furthermore, we incorporate GAT into deep Q network (DQN) and correspondingly design an intelligent resource management strategy for NS. Finally, we verify the superiority of the GAT-based DQN algorithm through extensive simulations.
Deep Learning-Based User Clustering For Mimo-Noma Networks

The user clustering problem in an uplink MIMO Non-Orthogonal Multiple Access (NOMA) scheme is considered here. The receiver is assumed to operate in two sequential stages that employ Linear Minimum Mean Squared Error (LMMSE) receivers. At the first stage, the receiver is designed to recover the transmission from a cluster of selected users/nodes. The contribution of these users is then subtracted from the received signal and the remaining user transmissions are then linearly recovered. The determination of which users should be detected during the first stage is formulated as a deep learning based multiple classification problem. In order to guarantee that the selection is robust to fast fading, the input to the neural network is based on second order channel statistics. Furthermore, the training process is simplified by using a large system approximation of the resulting sum-rates. Simulation results indicate that the proposed deep learning-based solution is able to achieve a significant rate advantage with respect to other lazy approaches, such as fixed or random cluster assignments.
Darstellung und Eigenschaften von Bis(phthalocyaninato)lanthanaten und -ceraten

High yields o f bisphthalocyaninates o f lanthanum and cerium have been obtained in the strongly exothermic reaction o f the dehydrated lanthanoid acetates with molten 1,2-dicyanobenzene in the presence o f potassium hydroxide or methylate. Salts o f the type (cat)[M (Pc(2-))-,] (M = La, Ce) with different cations (cat+ = K. Bu4N, PNP. TDOA) have been isolated. The corresponding “Hydrogen salts” are obtained by thermal decomposition of (Bu4N)[M(Pc(2-))-,] at T > 350 C. The dimeric structure is confirmed by negative fast atom bombardement mass spectra. The redox properties have been investigated by cyclovoltammetry and UV, VIS, MIR, FIR and resonance Raman (RR) spectra are reported. Electronic transitions between 2000 and 3000 cm 1 are observed in the low temperature RR spectra of (Bu4N)[Ce(Pc(2-))^] being RR enhanced at 470 nm. From the assignment to the higher transi­ tions within the symmetry split 5F5/2, :F7 manifolds o f the f1 ground state o f Ce3+ the crystal field parameters f 4f = 610.5, B40 = 242.2 and B60 = 4.1 cm -1 have been determined.
DFT+U Study of Chemical Impurities in PuO2

We employ density functional theory to explore the effects of impurities in the fluorite crystal structure of PuO2. The impurities that were considered are known impurities that exist in metallic δ-phase Pu, including H, C, Fe, and Ga. These impurities were placed at various high-symmetry sites within the PuO2 structure including an octahedral interstitial site, an interstitial site with coordination to two neighboring O atoms, an O substitutional site, and a Pu substitutional site. Incorporation energies were calculated to be energetically unfavorable for all sites except the Pu substitutional site. When impurities were placed in a Pu substitutional site, complexes incorporating the impurities and O formed within the PuO2 structure. The observed defect-oxygen structures were OH, CO3, FeO5, and GaO3. The presence of these defects led to distortion of the surrounding O atoms within the structure, producing long-range disorder of O atoms. In contrast, perturbations of Pu atoms had a relatively short-range e.
Fabrication of high performance oxygen sensors using multilayer oxides with high interfacial conductivity

The effective enhancement of the ionic conductivity of solid oxide electrolytes by manipulating the multilayered hetero-nanostructures has been recognized for more than a decade; however, such fantastic nanostructures have not been applied for practical applications yet. Here we fabricated Ce0.8Sm0.1Nd0.1O2−δ/Al2O3 (SNDC/AO) multilayered electrolyte materials with high oxygen ionic conductivity and explored their applications in oxygen sensors with low operating temperature. The multilayer oxide electrolytes show a conductivity of 2 orders of magnitude higher than that of traditional yttria-stabilized zirconia (YSZ) ceramics at 400 °C, which endows the sensors with high performances including a rapid response (∼0.1 s), high sensibility (down to 1 vol%) and high cycling stability (no performance degradation after 1000 cycles), and most importantly, low operating temperature (200 °C lower relative to YSZ-based sensors). The excellent performances of our multilayered electrolytes can be attributed to their high interfacial conductivity and low activation energy which might be related to the highly disordered microstructures. This study shows good prospects for the efficient and practical use of multilayered oxide-based electrolytes for a range of applications including sensors, oxygen separation, solid oxide fuel cells (SOFCs) and solid oxide electrolysis cells (SOECs).
Remittances and Industrialization in Africa: Evidence from Manufacturing Firms Data

RÉSUMÉ In this paper, we examine the effect of sub-Saharan Africa’s new main source of external finance,namely remittances, on industrialization. Using a fixed-effects instrumental variable approach andfirm survey data, we first find that international remittances increase both capital acquisition bynationals in existing manufacturing firms (intensive margin) and the entry of new manufacturingfirms into the market (extensive margin). Second, the results show a negative effect of internationalremittances on the sales of manufacturing firms. Third, a positive effect of international remittanceson employment in manufacturing firms is highlighted. Finally, the results are robust to the changeof remittances’ measure and the exclusion of over-represented and most industrialized countries.