Miracle-dz/UniFAR-FTUs huggingface dataset:
In vivo Immunomodulatory Potential of Aqueous Extract of Different parts of Terminalia catappa L.

Modulation of immunity is the most sought therapeutic effect as many human ailments arise because of imbalance in immune mechanisms. In the current corona virus disease scenarios also, the role of immunity to combat the dreadful virus has been well emphasized. Hence the present study aims at evaluating the immunomodulatory potential of aqueous extract obtained from the different parts such as bark, fruit and wood of Terminalia catappa. Based on the results obtained in acute oral toxicity and dose fixation studies, medium dose (250 mg/kg body weight) of selected plant extracts were administered for 14 d to swiss albino mice to evaluate nonspecific (Neutrophil adhesion, Phagocytic index) and specific (Hemagglutination antibody titer, Delayed type hypersensitivity) immunomodulatory properties. The results obtained for plant extract treated groups were compared with cyclophosphamide (immunosuppressant) treated and levamisole (immunostimulant) treated mice. From the data of the results obtained it could be concluded that selected parts of Terminalia catappa have immune stimulatory as well as anti-inflammatory properties, thereby proving their efficacy as true immunomodulators. Among the parts selected, fruits exhibited significant immunomodulatory potential followed by bark and wood.
The effect of geometric confinement on gas separation characteristics of additive poly[3-(trimethylsilyl)tricyclononene-7]

E. A. Chernova, M. A. Bermeshev, D. I. Petukhov, O. V. Boytsova, A. V. Lukashin, A. A. Eliseev Lomonosov Moscow State University, Leninskiye Gory, Moscow, 119991, Russia A. V. Topchiev Institute of Petrochemical Synthesis (TIPS) Russian Academy of Sciences, Leninsky prospect, 29, Moscow, 119991, Russia Kurnakov Institute of General and Inorganic Chemistry, Russian Academy of Sciences, Leninsky prospect, 31, Moscow, 119991, Russia
One-minute self-assembly of millimetre-long DAST crystalline microbelts via substrate-supported rapid evaporation crystallization

In this work, we propose a substrate-supported rapid evaporation crystallization (SSREC) method to rapidly self-assemble microbelts of 4-N,N-dimethylamino-4′-N′-methyl-stilbazolium tosylate (DAST), a benchmark organic nonlinear optical (NLO) crystal. The DAST microbelts formation depends very largely on substrate property and surfactant, and millimetre-long microbelts can be fabricated in less than one minute. The self-assembly driving forces are presumed to be the coulombic interactions which originate from DAST's ionic molecular structure and the large dipole moment of DAST nanocrystals. The DAST microbelt has a second harmonic generation active crystal structure and exhibits featured absorption and fluorescent properties. We believe that all these findings will facilitate applications of DAST in a very broad range of areas such as integrated light modulation, lasing etc. Furthermore, the simplicity of the SSREC may open new avenues in the area of organic NLO one-dimensional materials fabrication.
The Kjeldahl Titrimetric Finish: On the Ammonia Titration Trapping in Boric Acid

Kjeldahl method using concentrated boric acid is a common practice in many laboratories. A thorough study of the titration with hydrochloric acid of ammonia trapped in a solution of boric acid is made in an attempt to explain the fundamentals of a widely applied standard method. A new potentiometric method for the determination of the end point in the Kjeldahl titrimetric finish is proposed based on the linearization of the titration curve of the ammonia-boric acid system. The method is strictly based on mole and charge balances, and no approximations are made in deriving the equations. The proposed method has proved very accurate when applied to synthetic titration curves and data. Some problems, however, are experienced in the practice, because the behavior of the experimental system studied is far from the expected one on the basis of the theoretical model. However, a slight modification of the devised method has been applied to the experimental titration of ammonia with hydrochloric acid, in boric acid as trapping solution, to get good results.
In silico Study of the Interaction between the Modified B-ring Analogues of Colchicine with Tubulin Heterodimer

Theoretical investigation of the interaction between the modifications at the C-5, C-6, and C-7 positions of the B-ring of colchicine and tubulin heterodimer has been investigated by using the molecular docking simulation. The docking results provide the energetic and structural information in terms of the binding energy, binding affinity, hydrogen bonding, and conformations of docked ligand poses with residues within colchicine binding site. Overall results show that the modified C-5 (in Model A ) and C-7 (in Model C ) of B-ring analogues give the highest binding affinities to tubulin, whereas all lowest-affinity isomers belong to the C-6 substituents (in Model B ). As expected, the docked ligands of the C-5, C-6, and C-7 of B-ring analogues which are located at the a/b intradimer interface of tubulin were shifting toward the a-subunit binding space to form drug-tubulin complexes. Keywords : colchicine, B-ring analogues, tubulin, binding affinity, molecular docking
SYNERGISTIC CO-CULTIVATION OF ACTIVATED SLUDGE AND MICROALGAE IN ENHANCING LIPID PRODUCTION AND N-LADEN WASTEWATER TREATMENT

The influence of inoculation ratios of activated sludge and microalgae were investigated in this study in the aspects of biomass yield, lipid yield and total nitrogen (TN) removal efficiency. It was observed that mixed culture of activated sludge/microalgae with the ratio 1:1 and 1:0.75 achieved a maximum lipid production up to 0.144 g/L and 0.133 g/L as compared with microalgae culture alone, which was only 0.081 g/L. The highest total nitrogen (TN) removal was observed with 1:1 and 1:0.75 ratios of activated sludge/microalgae cultures ranging from 96.3-96.9% removal efficiency, which was an improvement of about 90% removal efficiency compared to the activated sludge culture (6.25±0.08%). The flocculation efficiency was generally improved in mixed cultures of activated sludge andmicroalgae in comparison with only activated sludge culture and microalgae culture alone. Keywords : activated sludge; microalgae; co-cultivation; lipid; nitrogen removal.
A Reinforcement-Learning-Based Secure Demand Response Scheme for Smart Grid System

Smart grid (SG) systems necessitate secure demand response management (DRM) schemes for real-time decisions making to increase the effectiveness and stability of SG systems along with data security. Motivated from the aforementioned discussion, in this article, we propose Q-SDRM, a secure DRM scheme for home energy management (HEM) using reinforcement learning (RL) and ethereum blockchain (EBC) to facilitate energy consumption reduction and decrease energy costs. In cooperation with RL, $Q$ -learning is adopted to make optimal price decisions using Markov decision process (MDP) to reduce energy consumption, which benefits both consumers and utility providers. Then, Q-SDRM uses ethereum smart-contract (ESC) to deal with data security issues and incorporate with off-chain storage interplanetary file system (IPFS) that handles data storage costs issue. Experimental results reveal the effectiveness of the proposed Q-SDRM scheme, which significantly reduces energy consumption and energy cost. The proposed scheme also provides secure access to energy data in real time compared with state-of-the-art approaches regarding different evaluation metrics, such as scalability, overall energy cost, and data storage cost.
Assessment of morning sleep propensity with lemborexant in adults with insomnia disorder in a randomized, placebo-controlled crossover study

Abstract Objective To evaluate effects of lemborexant (LEM), a dual orexin receptor antagonist, on next-morning sleep propensity assessed by a modified Multiple Sleep Latency Test (M-MSLT) in adults with insomnia disorder. Methods Study 107 (E2006-A001-107) was a phase 1, randomized, double-blind, four-period crossover study. Subjects (n = 69) received oral single-dose placebo, LEM 5 mg (LEM5), and LEM 10 mg (LEM10) at bedtime in periods 1–3 in a randomized crossover and open-label flurazepam 30 mg in period 4. After an 8-hour overnight sleep opportunity, the M-MSLT measured average sleep onset latency (SOL). Mean change from baseline in average SOL versus placebo of −6.0 min or more was considered clinically meaningful. Other sleep propensity assessments included the proportion of subjects with average SOL >6 min shorter than placebo. LEM plasma concentrations, safety, and tolerability were also assessed. Results M-MSLT assay sensitivity was confirmed by a clinically meaningful decrease in average SOL with flurazepam versus placebo (least squares mean [LSM] difference –6.06 min; 1-sided p < 0.0001). In contrast, decreases in average SOL with LEM5 (LSM difference vs. placebo –1.15 min; 1-sided p = 0.0262) and LEM10 (–3.48 min; p < 0.0001) did not meet the predefined threshold for a clinically meaningful effect (LEM5, –2.12; LEM10, –4.46). Some individuals did experience higher sleep propensity (average SOL >6.0 min shorter than placebo), particularly with LEM10 (LEM10, 29.4%; LEM5, 13.2%). Conclusions In contrast to flurazepam, LEM5 and LEM10 did not show clinically meaningful mean increases in next-morning sleep propensity versus placebo. The possibility that some subjects may experience residual morning effects cannot be excluded. Clinical trial registration: ClinicalTrials.gov, NCT02350309
Scalings in homogenisation of reaction, diffusion and interfacial exchange in a two-phase medium

We consider the homogenisation of a coupled system of parabolic partial differential equations in a heterogeneous two-phase medium and study various choices of scaling of the material parameters with powers of the homogenisation parameter. The system may be regarded as modelling a reaction–diffusion problem, the Stokes problem of single-phase flow of a slightly compressible fluid or as a heat conduction problem (with or without interfacial resistance). A proper nondimensionalisation shows that, depending on the ratio of the characteristic diffusion times of the different species, different scalings of the diffusivities and the interfacial-exchange coefficient with the scale parameter ε appear reasonable. It is shown that, starting with the same type of problem on the microscopic scale, different choices of scaling of the diffusion coefficients (resp. permeability or conductivity) and the interfacialexchange coefficient lead to different types of macroscopic systems of equations in the limit. In a unified approach, the limit problems are classified for a whole range of scaling parameters. New limit problems arise and well-known results from the literature are recovered as special cases for certain scalings such as the models of Barenblatt et. al and Arbogast et. al for single-phase flow.
First-Principles Investigation of Lithium Polysulfide Structure and Behavior in Solution

The lithium–sulfur battery is a promising next generation energy storage technology that could meet the demands of modern society with a theoretical specific energy near 2500 W h kg–1. However, this battery chemistry faces unique problems such as the parasitic polysulfide shuttle reaction, which hinders battery performance severely. This shuttle phenomenon is caused by solubilities of intermediate reaction products in the electrolyte during the reduction chemistry of the battery. With molecular simulation and computational chemistry tools, we studied the thermodynamics, solvation structure, and dynamics of the long-chain lithium polysulfide species Li2S6 and Li2S8 in dimethoxyethane and 1,3-dioxolane to gain a deeper fundamental understanding of this process. We determined the structure of the first solvation shell for Li+ as well as those of Li2S6, Li2S8 closed, and Li2S8 linear in pure solvents and solvents with extra Li+ added. The lithium polysulfide species were found not to favor dissociation and wo.
Entwicklung chemometrischer Methoden für die Klassifikation von Bakterien mittels Mikro-Raman-Spektroskopie

In der vorliegenden Dissertation wurde ein datenanalytisches Auswertungssystem fur die Mikro-Raman-spektroskopische Identifizierung von Bakterien in industriellen Reinraumen entwickelt. Das Auswertungssystem setzt sich zusammen aus Spektrenvorbehandlung, Klassifikation und Erkennung von Vorhersageausreisern. Auf der Basis eines hochdiversen Datensatzes, der aus 3642 Spektren und 29 Bakterienstammen besteht, wurde zunachst die Leistungsfahigkeit verschiedener Methoden zur Spektrenvorbehandlung bewertet. Da man Bakterien in ihrer naturlichen Umgebung in verschiedenen Wachstumsphasen und Stoffwechselzustanden vorfindet, sind die Bakterien eines Stammes haufig sehr heterogen. „Gaussian Mixture” Diskriminanzanalyse (MDA) stellt eine ideale Klassifikationsmethode fur diese Aufgabe dar, da mittels MDA auch heterogene und streuende Klassenstrukturen modelliert werden konnen. Die Nutzlichkeit der MDA fur die Differenzierung der Bakterienstamme wurde im Vergleich zu verschiedenen linearen und nichtlinearen Klassifikationsmethoden demonstriert. Zu den verwendeten Algorithmen zahlen neben MDA „Partial Least Squares“ –Distriminanzanalyse (PLS-DA), Lineare Diskriminanzanalyse (LDA), Quadratische Diskriminanzanalyse (QDA), k-nachste Nachbarn Klassifizierer (kNN) und „Support Vector Machines“ (SVMs). Die Vorhersagegenauigkeit der MDA konnte durch deutlich gesteigert werden, indem MDA mit einer paarweisen Klassifikation kombiniert wurde. Dabei wurde das Multiklassenproblem in mehrere Zweiklassenprobleme aufgeteilt. Die Ergebnisse wurden anschliesend durch eine „Major Vote“-Entscheidung kombiniert. Mit diesem paarweisen Ansatz konnten 86.6% der Spektren richtig klassifiziert werden. Neben der hohen Vorhersagegenaugkeit wurden in der Arbeit weitere Vorteile der paarweisen MDA fur die gegebene Aufgabenstellung aufgezeigt. Dazu zahlen der leichte Zugang zu a posteriori Wahrscheinlichkeiten, die zuverlassige Erkennung von Vorhersageausreisern und die Interpretierbarkeit des Modells.
Effectiveness of Motion Infographic Media on the Improvement of Knowledge and Medical Adherence in Human Immunodeficiency Virus Patients

The study aimed to examine the effectiveness of motion infographic media on improving patient’s knowledge and medical adherence during counseling. Eighty eight human immunodeficiency virus infected patients from outpatient department, human immunodeficiency virus clinic, Saraburi hospital participated in the study. Subjects were randomized into control and study groups (44 of each). Subjects in the study group received motion infographic media, while those in the control group did not receive motion infographic media. The results showed that subjects in the study group had higher knowledge scores and higher percentage of medical adherence than those in the control group in all tests. In addition, knowledge and medical adherence after receiving motion infographic media in the study group were even greater as indicated by higher knowledge test scores and higher percentage of medical adherence, as compared to before receiving the motion infographic media. It can be concluded that motion infographic media is beneficial and can be used as a tool for improving patient’s knowledge and medical adherence during counseling.
Financing the Small and Medium Enterprises in Post COVID- 19 Nigerian Economies: Issues and Perspectives

: The purpose of this paper is to explore the financing needs of Small and Medium Enterprises in the Post COVID-19 Nigeria Economy. The present state of the Economy was reviewed to determine how the pandemic has affected both the economy and the SMEs.Also a study to determine financing gaps of the SMEs in Nigeria using the simple descriptive means and standard deviations was carried out. The study is based on a sample of 150 small business owners across different sectors (Trade, Services, ICT, Education, and Hospitability) in Port Harcourt Rivers State. The results show that SMEs have financing gaps that are demand related. Consistent with previous studies, the results show that risk aversion, desire to maintain control and reputational effects are key factors explaining the demand-side financing gaps of SMEs in Nigeria. An outlook of the post COVID-19 era projects a weak economy that would struggle to recover. This paper concludes that SMEs that are already faced with demand related financing gaps and aggravated by low sales and supply chain shocks caused by the pandemic should be more strategic in pursuing their financing needs in the wake of post COVID-19 dwindling economy. To strengthen and enhance the capabilities of SMEs, recommendations are made to both the SMEs and the Monetary Authorities.
The Smart Intersection: A Solution to Early-Stage Vehicle-to-Everything Deployment

Connected vehicles and connected infrastructure technology are being deployed globally. Although the connectivity technology has a demonstrated capability of aiding collision prevention, the safety benefits are not maximized because of the limited coverage during the early deployment phase. Honda’s “smart intersection” research has led the company to a pilot deployment utilizing a state-of-the-art artificial intelligence solution in infrastructure sensing technology. This sensing technology employs a vision processing system to detect and differentiate nonconnected road users, including automobiles, emergency vehicles, motorcycles, and pedestrians. The detected object types are packaged into standardized wireless vehicle-to-vehicle (V2V) safety messages. These messages are transmitted from the roadside infrastructure to nearby connected vehicles. This article first discusses a few challenges associated with infrastructure sensing and collective perception and introduces techniques that ensure the infrastructure-generated V2V data transmissions are delivered in a real-time manner and with high message accuracy. We then examine the solutions through actual implementation accuracy assessments.
A Hybrid Deep Learning Intrusion Detection Model for Fog Computing Environment

Fog computing extends the concept of cloud computing by providing the services of computing, storage, and networking connectivity at the edge between data centers in cloud computing environments and end devices. Having the intelligence at the edge enables faster real-time decision-making and reduces the amount of data forwarded to the cloud. When enhanced by fog computing, the Internet of Things (IoT) brings low latency and improves real time and quality of service (QoS) in IoT applications of augmented reality, smart grids, smart vehicles, and healthcare. However, both cloud and fog computing environments are vulnerable to several kinds of attacks that can lead to unexpected loss. For example, a denial of service (DoS) attack can block authenticated users by rendering network resources unavailable and consuming network bandwidth unnecessarily. This paper proposes an intrusion classification model using a convolutional neural network (CNN) and Long Short-Term Memory networks (LSTM) to obtain the advantages of deep learning methods in order to accurately predict such attacks. The proposed integrated CNN with LSTM-based Fog Computing Intrusion Detection ICNN-FCID model is used for multi-class attack classification. Our proposed model is demonstrated using NSL-KDD, a benchmark dataset, and provides attack detection accuracy of about 96.5%. Comparisons of the accuracy of our model with both traditional and other recent deep learning approaches show that our model is superior in performance. The ICNN-FCID model can be used in fog layer devices where network traffic is monitored and the attacks are detected. As a result, the cloud server and fog layer devices can be protected from malicious users and are always available in providing services to IoT devices.
Research on Virtual Reality Technology in Public Art Creation

With the continuous update and progress of computer technology, there are more and more display ways in public environment, and many high-tech ways such as virtual reality are also integrated into the display of public environment design. Its interactive, comprehensive and realistic features enhance the artistic sense of the whole design. Public art creation is a kind of diversified art design that includes different disciplines. Its main carrier is the display of environment and culture, which involves a wide range of fields and can better meet the people’s pursuit of sensory stimulation in modern society. Therefore, this paper will make an in-depth analysis of the application of virtual reality technology in public art creation, and briefly describe its design principle and its application mode, in order to provide some valuable opinions for future practice creation.
Structural Stability of Iodide Perovskite: A Combined Cluster Expansion Method and First-Principles Study

To aid the development of Pb-free perovskite solar cells, the stability of the iodide perovskite structure ABI3 has been investigated by first-principles calculations, Bader charge analysis, and the cluster expansion method. At the A sites, methylammonium (MA, CH3NH3+), formamidinium (FA, CH(NH2)2+), and Cs+ were modeled, while at the B sites, one or two elements from Pb, Sn, Ge, In, Ga, Bi, and Sr were examined. For the partially substituted system A(B,B′)I3, we found that the stability strongly depends on the identity of the A-site cation. For example, Cs(B,B′)I3 structures are stabilized by a mixture of divalent cations, such as Pb, Sn, and Ge, at the B site. Concerning the stabilization mechanisms, Coulomb energy gain seems to be the origin of the structural stability in A = Cs structures. From our results, Cs(B,B′)I3, where the B site is occupied by divalent cations, are possible candidates for high stability, lead-free solar cell materials.
Determination of selected toxic metal (As, Cd, Pb) and essential (Zn, Cu) elements in local canned seafood products

In this study, the concentrations of selected toxic metals (Pb, As, Cd) and essential elements (Zn, Cu) of local canned seafood including sardines, tuna, anchovies, shellfish (mussels and cockles), prawns, mackerel and cuttlefish were determined. All 30 samples were purchased from supermarkets in Nilai, Negeri Sembilan. The highest concentration of trace metals in all samples was Zn which is 38.96±0.56 mg/kg, followed by Cu (2.40±0.57 mg/kg), Pb (1.71±0.71 mg/kg), As (0.96±0.70 mg/kg) and Cd (0.25±0.70 mg/kg). The average concentration of toxic elements were the highest in anchovy species with concentration of 6.93 mg/kg followed by shellfish (4.24 mg/kg), mixed seafood (4.17 mg/kg), cuttlefish (3.63 mg/kg), prawns (3.28 mg/kg), sardines (2.65 mg/kg), tuna (1.68 mg/kg) and the lowest which is mackerel (1.36 mg/kg). The results were compared with the previous studies.In this study, the concentrations of selected toxic metals (Pb, As, Cd) and essential elements (Zn, Cu) of local canned seafood including sardines, tuna, anchovies, shellfish (mussels and cockles), prawns, mackerel and cuttlefish were determined. All 30 samples were purchased from supermarkets in Nilai, Negeri Sembilan. The highest concentration of trace metals in all samples was Zn which is 38.96±0.56 mg/kg, followed by Cu (2.40±0.57 mg/kg), Pb (1.71±0.71 mg/kg), As (0.96±0.70 mg/kg) and Cd (0.25±0.70 mg/kg). The average concentration of toxic elements were the highest in anchovy species with concentration of 6.93 mg/kg followed by shellfish (4.24 mg/kg), mixed seafood (4.17 mg/kg), cuttlefish (3.63 mg/kg), prawns (3.28 mg/kg), sardines (2.65 mg/kg), tuna (1.68 mg/kg) and the lowest which is mackerel (1.36 mg/kg). The results were compared with the previous studies.