Prevalence of multi-drug resistant bacteria in intensive care units at Tripoli University Hospital, Tripoli, Libya.

Among hospitalized patients worldwide, infections caused by multidrug-resistant (MDR) bacteria are a major cause of morbidity and mortality. This study aimed to isolate MDR bacteria from five intensive care units (ICUs) at Tripoli University Hospital (TUH). A prospective cross-sectional study was conducted over a seven-month period (September 2022 to March 2023) across five ICUs at TUH. A total of 197 swabs were collected from Patients', healthcare workers' and ICUs equipment. Samples collected from patients were nasal swabs, oral cavity swabs, hand swabs, sputum specimens, skin swabs, umbilical venous catheter swabs, and around cannula. Swabs collected from health care workers were nasal swabs, whereas ICUs equipment's samples were from endotracheal tubes, oxygen masks, and neonatal incubators. Identification and antimicrobial susceptibility test was confirmed by using MicroScan auto SCAN 4 (Beckman Coulter). The most frequent strains were Gram negative bacilli 113 (57.4%) with the predominance of Acinetobacter baumannii 50/113 (44%) followed by Klebsiella pneumoniae 44/113 (40%) and Pseudomonas aeruginosa 6/113 (5.3%). The total Gram positive bacterial strains isolated were 84 (42.6%), coagulase negative Staphylococci 55 (66%) with MDRs (89%) were the most common isolates followed by Staphylococcus aureus 15 (17.8%). Different antibiotics were used against these isolates; Gram- negative isolates showed high resistance rates to ceftazidime, gentamicin, amikacin and ertapenem. A. baumannii were the most frequent MDROs (94%), and the highest resistance rates in Gram-positive strains were observed toward ampicillin, oxacillin, ampicillin/sulbactam and Cefoxitin, representing 90% of total MDR Gram-positive isolates. ESBL and MRS were identified in most of strains. The prevalence of antibiotic resistance was high for both Gram negative and Gram positive isolates. This prevalence requires strict infection prevention and control intervention, continuous monitoring, implementation of effective antibiotic stewardship, immediate, concerted and collaborative action to monitor its prevalence and spread in the hospital.

Sparse-Stochastic Fragmented Exchange for Large-Scale Hybrid Time-Dependent Density Functional Theory Calculations.

We extend our recently developed sparse-stochastic fragmented exchange formalism for ground-state near-gap hybrid DFT to calculate absorption spectra within linear-response time-dependent generalized Kohn-Sham DFT (LR-GKS-TDDFT) for systems consisting of thousands of valence electrons within a grid-based/plane-wave representation. A mixed deterministic/fragmented-stochastic compression of the exchange kernel, here using long-range explicit exchange functionals, provides an efficient method for accurate optical spectra. Both real-time propagation as well as frequency-resolved Casida-equation-type approaches for spectra are presented, and the method is applied to large molecular dyes.

Efficient Quasiparticle Determination beyond the Diagonal Approximation via Random Compression.

Calculations of excited states in the Green's function formalism often invokes the diagonal approximation, in which the quasiparticle states are taken from a mean-field calculation. In this paper, we extend the stochastic approaches applied in the many-body perturbation theory and overcome this limitation for large systems in which we are interested in a small subset of states. We separate the problem into a core subspace whose coupling to the remainder of the system environment is stochastically sampled. This method is exemplified on computing hole injection energies into CO2 on an extended gold surface with nearly 3000 electrons. We find that in the extended system the size of the problem can be compressed up to 95% using stochastic sampling. This result provides a way forward for self-consistent stochastic methods and determination of Dyson orbitals in large systems.

Velocity-Gauge Real-Time Time-Dependent Density Functional Tight-Binding for Large-Scale Condensed Matter Systems.

We present a new velocity-gauge real-time, time-dependent density functional tight-binding (VG-rtTDDFTB) implementation in the open-source DFTB+ software package (https://dftbplus.org) for probing electronic excitations in large, condensed matter systems. Our VG-rtTDDFTB approach enables real-time electron dynamics simulations of large, periodic, condensed matter systems containing thousands of atoms with a favorable computational scaling as a function of system size. We provide computational details and benchmark calculations to demonstrate its accuracy and computational parallelizability on a variety of large material systems. As a representative example, we calculate laser-induced electron dynamics in a 512-atom amorphous silicon supercell to highlight the large periodic systems that can be examined with our implementation. Taken together, our VG-rtTDDFTB approach enables new electron dynamics simulations of complex systems that require large periodic supercells, such as crystal defects, complex surfaces, nanowires, and amorphous materials.

A Comparative GC/MS Analysis of Citrus Essential Oils: Unveiling the Potential Benefits of Herb-Drug Interactions in Preventing Paracetamol-Induced Hepatotoxicity.

Our study aimed to test the potential of Citrus oils in protecting against paracetamol (PAR)-induced hepatotoxicity. The essential oils of Pineapple sweet orange (OO), Murcott mandarin (MO), Red grapefruit (GO), and Oval kumquat (KO) were investigated using gas chromatography coupled with mass spectrometry (GC/MS). Twenty-seven compounds were identified, with monoterpene hydrocarbons being abundant class. d-Limonene had the highest percentage (92.98 %, 92.82 %, 89.75 %, and 94.46 % in OO, MO, GO, and KO, respectively). Hierarchical cluster analysis (HCA) and principal components analysis (PCA) revealed that octanal, linalool, germacrene D, and d-limonene were the principal discriminatory metabolites that segregated the samples into three distinct clusters. In vitro antioxidant capacities were ranged from 1.2-12.27, 1.79-5.91, and 235.05-585.28 µM Trolox eq/mg oil for 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic (ABTS), ferric-reducing antioxidant power (FRAP), and oxygen radical absorbance capacity (ORAC), respectively. In vivo, citrus oils exhibited a significant reduction in alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), and nitric oxide (NO). Additionally, there was an increase in glutathione reductase (GSH), and the liver architecture was nearly normal. Molecular docking revealed that d-limonene exhibited a good inhibitory interaction with cytochrome P450 (CYP450) isoforms 1A2, 3A4, and 2E1, with binding energies of -6.17, -4.51, and -5.61 kcal/mol, respectively.

Taming Food-Drug Interaction Risk: Potential Inhibitory Effects of Citrus Juices on Cytochrome Liver Enzymes Can Safeguard the Liver from Overdose Paracetamol-Induced Hepatotoxicity.

Paracetamol overdose is the leading cause of drug-induced hepatotoxicity worldwide. Because of N-acetyl cysteine's limited therapeutic efficacy and safety, searching for alternative therapeutic substitutes is necessary. This study investigated four citrus juices: Citrus sinensis L. Osbeck var. Pineapple (pineapple sweet orange), Citrus reticulata Blanco × Citrus sinensis L. Osbeck (Murcott mandarin), Citrus paradisi Macfadyen var. Ruby Red (red grapefruit), and Fortunella margarita Swingle (oval kumquat) to improve the herbal therapy against paracetamol-induced liver toxicity. UHPLC-QTOF-MS/MS profiling of the investigated samples resulted in the identification of about 40 metabolites belonging to different phytochemical classes. Phenolic compounds were the most abundant, with the total content ranked from 609.18 to 1093.26 µg gallic acid equivalent (GAE)/mL juice. The multivariate data analysis revealed that phloretin 3',5'-di-C-glucoside, narirutin, naringin, hesperidin, 2-O-rhamnosyl-swertisin, fortunellin (acacetin-7-O-neohesperidoside), sinensetin, nobiletin, and tangeretin represented the crucial discriminatory metabolites that segregated the analyzed samples. Nevertheless, the antioxidant activity of the samples was 1135.91-2913.92 µM Trolox eq/mL juice, 718.95-3749.47 µM Trolox eq/mL juice, and 2304.74-4390.32 µM Trolox eq/mL juice, as revealed from 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid, ferric-reducing antioxidant power, and oxygen radical absorbance capacity, respectively. The in vivo paracetamol-induced hepatotoxicity model in rats was established and assessed by measuring the levels of hepatic enzymes and antioxidant biomarkers. Interestingly, the concomitant administration of citrus juices with a toxic dose of paracetamol effectively recovered the liver injury, as confirmed by normal sections of hepatocytes. This action could be due to the interactions between the major identified metabolites (hesperidin, hesperetin, phloretin 3',5'-di-C-glucoside, fortunellin, poncirin, nobiletin, apigenin-6,8-digalactoside, 6',7'-dihydroxybergamottin, naringenin, and naringin) and cytochrome P450 isoforms (CYP3A4, CYP2E1, and CYP1A2), as revealed from the molecular docking study. The most promising compounds in the three docking processes were hesperidin, fortunellin, poncirin, and naringin. Finally, a desirable food-drug interaction was achieved in our research to overcome paracetamol overdose-induced hepatotoxicity.

Effect of Si Content on the Thermal Expansion of Ti15Mo(0-2 Si) Biomaterial Alloys during Different Heating Rates.

Thermal expansion measurements were used to characterize phase transformations in metastable ß-Ti alloys (Ti15MoxSi) without and with various Si additions (where x = 0, 0.5, 1.0, 1.5, and 2 in wt.%) during linear heating at two heating rates of 5 and 10 °C/min up to 850 °C. For this study, five alloys were developed and examined in terms of their presence phases, microstructures, and starting and final transformation temperatures. According to the results, all of the as-cast samples primarily include an equiaxed ß-Ti phase. The influence of phase transformation on the material dimensions was discussed and compared with the variations in Si contents. The transformation was investigated using a dilatometric technique for the developed alloys during continuous heating and cooling. The dilatometric curve of heating revealed two distinct reflection points as the heating temperature increased. The starting transformation temperature (Ts) to obtain the ω-phase was reported at 359 °C without Si addition; whereas the final transformation temperature (Tf) of the dissolution of α-phase was obtained at 572 °C at a heating rate of 10 °C/min. At 2 wt.% Si, the first derivative curves reported Ts and Tf transforming temperatures of 314-565 °C (at a 5 °C/min heating rate) and 270-540 °C (at a 10 °C/min heating rate), respectively. The Ts and Tf transforming temperatures were significantly decreased with Si additions, which decreased the ß-transus temperature. Moreover, the thermal expansion coefficient curves of the investigated alloys without and with 2 wt.% Si were studied. The transformation heating curves have an S-shaped pattern, according to the results.

Worn surface topography and mathematical modeling of Ti-6Al-3Mo-2Sn-2Zr-2Nb-1.5Cr alloy.

This study aims at investigating worn surface topography and mathematical modeling of annealed Ti-6Al-3Mo-2Sn-2Zr-2Nb-1.5Cr alloy using response surface methodology (RSM). The alloy was subjected to three different regimes in order to study their effect on mechanical properties. First regime was applying cold deformation by compression until 15% drop in height at room temperature. The second regime was performing solution treated on the deformed samples at 920 °C for 15 min then air-cooled (AC) to ambient temperature. Third regime was applying aging on the deformed and solution treated specimen for 4 hr at 590 °C followed by air-cooling. Three different velocities (1, 1.5, and 2 m/s) were adopted to conduct dry sliding wear according to the experimental design technique (EDT). Gwyddion and Matlab softwares were used to detect worn surface photographs analytically and graphically. Maximum hardness of 425 HV20 was obtained for AC+Aging specimen, while minimum hardness of 353 HV20 was reported for the annealed specimen. Applying aging process after solution treatment enhanced considerably the wear property and this enhancement reached 98% as compared to the annealed condition. The relationship between input factors (hardness & velocity) and responses (Abbott Firestone zones) was demonstrated using analysis of variance (ANOVA). The best models for Abbott Firestone zones (high peaks, exploitation, and voids) produced accurate data that could be estimated for saving time and cost. The results showed that the average surface roughness increases with increasing sliding velocity for all conditions except AC+Aging condition where the average surface roughness decreased with increasing sliding velocity. The results revealed that at low velocity and hardness, the material gives the highest exploitation zone (86%). While at high velocity and hardness, the material gives the lowest exploitation zone (70%). In general, the predicted results of mathematical model showed close agreement with experimental results, creating that models could be utilized to predict Abbott Firestone zones satisfactorily.

The incidence of radiation-induced moyamoya among pediatric brain tumor patients who received photon radiation versus those who received proton beam therapy: a systematic review.

Cranial irradiation is associated with several adverse events such as endocrinopathy, growth retardation, neurocognitive impairment, secondary malignancies, cerebral vasculopathy, and potential stroke. The better side effects profile of proton beam therapy compared with that of photon radiation therapy is due to its physical properties, mainly the sharp dose fall-off after energy deposition in the Bragg peak. Despite the better toxicity profile of proton beam therapy, the risk of  moyamoya syndrome still exists. We conducted a systematic review of the existing literature on moyamoya syndrome after receiving cranial radiation therapy for pediatric brain tumors to investigate the incidence of moyamoya syndrome after receiving photon versus proton radiation therapy. In this review, we report that the incidence of moyamoya syndrome after receiving proton beam therapy is almost double that of photon-induced moyamoya syndrome. Patients who received proton beam therapy for the management of pediatric brain tumors are more likely to develop moyamoya syndrome at the age of less than 5 years. Meanwhile, most patients with proton-induced moyamoya are more likely to be diagnosed within the first 2 years after the completion of their proton beam therapy.

Renal cell carcinoma management: real-world practice and challenges at a national level.

Renal cell carcinoma (RCC) management has seen a revolution over the last decades. Six Lebanese oncologists discussed recent updates in RCC management and outlined the challenges and future directions in Lebanon. Sunitinib continues to be a first-line choice for metastatic RCC in Lebanon, except for intermediate- and poor-risk patients. Immunotherapy is not always accessible to patients or selected routinely as first-line therapy. More data are needed on the sequencing of immunotherapy and tyrosine kinase inhibitor treatments and on the use of immunotherapy beyond progression and/or after failure of immunotherapy in the first-line setting. For second-line management, the clinical experience with axitinib for low tumor growth rate and nivolumab after progression on tyrosine kinase inhibitors make those two agents the most widely used. Several challenges affect the Lebanese practice, limiting the accessibility and availability of the medications. Reimbursement remains the most critical challenge, especially with the socioeconomic crisis of October 2019.

Optimized attenuated interaction: Enabling stochastic Bethe-Salpeter spectra for large systems.

We develop an improved stochastic formalism for the Bethe-Salpeter equation (BSE), based on an exact separation of the effective-interaction W into two parts, W = (W - vW) + vW, where the latter is formally any translationally invariant interaction, vW(r - r'). When optimizing the fit of the exchange kernel vW to W, using a stochastic sampling W, the difference W - vW becomes quite small. Then, in the main BSE routine, this small difference is stochastically sampled. The number of stochastic samples needed for an accurate spectrum is then largely independent of system size. While the method is formally cubic in scaling, the scaling prefactor is small due to the constant number of stochastic orbitals needed for sampling W.

WS2 and WS2-ZnO Chemiresistive Gas Sensors: The Role of Analyte Charge Asymmetry and Molecular Size.

We investigate the interaction of various analytes (toluene, acetone, ethanol, and water) possessing different structures, bonding, and molecular sizes with a laser-exfoliated WS2 sensing material in a chemiresistive sensor. The sensor showed a clear response to all analytes, which was significantly enhanced by modifying the WS2 surface. This was achieved by creating WS2-ZnO heterojunctions via the deposition of ZnO nanoparticles on the WS2 surface with a high-throughput, atmospheric-pressure spatial atomic layer deposition system. Water and ethanol produced a much higher response compared to acetone and toluene for both the WS2 and WS2-ZnO sensing mediums. We resolved that the charge-asymmetry points in analyte molecules play a key role in determining the sensor response. High charge-asymmetry points correspond to highly polar bonds (HPBs) in a neutral molecule that have a high probability of interaction with the sensing medium. Our results indicate that the polarity of the HPBs primarily dictates the interaction between the analyte and sensing medium and consequently controls the response of the sensor. Moreover, the size of the analyte molecule was found to affect the sensing response; if two molecules have the same HPBs and are exposed to the same sensing medium, the smaller molecule is likely to produce a higher and faster response. Our study provides a comprehensive picture of analyte-sensor interactions that can help in advancing semiconductor gas sensors, including those based on two-dimensional materials.

Bioactive fraction from Plumeria obtusa L. attenuates LPS-induced acute lung injury in mice and inflammation in RAW 264.7 macrophages: LC/QToF-MS and molecular docking.

In this study, the anti-inflammatory effects of the methanolic extract (TE) of Plumeria obtusa L. (aerial parts) and its fractions were evaluated in vitro, and active fraction was evaluated in vivo. Among tested extracts, dichloromethane fraction (DCM-F) exhibited the strongest inhibition of lipopolysaccharide (LPS)-induced nitric oxide (NO) in RAW 264.7 macrophages. The effect of DCM-F on LPS-induced acute lung injury (ALI) in mice was studied. The animals were divided into five groups (n = 7) randomly; Gp I: negative control, GP II: positive control (LPS group), GP III: standard (dexamethasone, 2 mg/kg b.wt), GP IV and V: DCM-F (100 mg/kg), and DEM-F (200 mg/kg), respectively. DCM-F at a dose of 200 mg/kg suppressed the ability of LPS to increase the levels of nitric oxide synthase (iNOS), NO, tumor necrosis factor-α (TNF-α), and interleukin 6 (IL-6), as measured by ELISA. In addition, the expression of cyclooxygenase-2 (COX-2) was reduced (determined by immunohistochemistry) and the level of malondialdehyde (MDA) was decreased while that of catalase was restored to the normal values. Furthermore, the histopathological scores of inflammation induced by LPS were reduced. Twenty-two compounds were tentatively identified in DCM-F using LC/ESI-QToF with iridoids, phenolic derivatives and flavonoids as major constituents. Identified compounds were subjected to two different molecular docking processes against iNOS and prostaglandin E synthase-1 target receptors. Notably, protoplumericin A and 13-O-coumaroyl plumeride were the most promising members compared to the co-crystallized inhibitor in each case. These findings suggested that DCM-F attenuates the LPS-induced ALI in experimental animals through its anti-inflammatory and antioxidant potential.

Bioassay-Guided Isolation of Antimicrobial Components and LC/QToF Profile of Plumeria obtusa: Potential for the Treatment of Antimicrobial Resistance.

The methanolic fraction (M-F) of the total extract (TE) of Plumeria obtusa L. aerial parts showed promising antibacterial effects against the MDR (multidrug-resistant) gram-negative pathogens Klebsiella pneumoniae and Escherichia coli O157:H7 [Shiga toxin-producing E. coli (STEC)]. In addition, M-F had a synergistic effect (in combination with vancomycin) against the MDR gram-positive strains MRSA (methicillin-resistant Staphylococcus aureus) and Bacillus cereus. After treating the K. pneumoniae- and STEC-infected mice with M-F (25 mg/kg, i.p.), the level of IgM and TNF-α was decreased and the severity of pathological lesions were reduced better than that observed after administration of gentamycin (33 mg/kg, i.p.). Thirty-seven compounds including 10 plumeria-type iridoids and 18 phenolics, 7 quinoline derivatives, 1 amino acid, and 1 fatty acid were identified in TE using LC/ESI-QToF. Furthermore, five compounds; kaempferol 3-O-rutinoside (M1), quercetin 3-O-rutinoside (M2), glochiflavanoside B (M3), plumieride (M4), and 13-O-caffeoylplumieride (M5) were isolated from M-F. M5 was active against K. pneumoniae (MIC of 64 µg/mL) and STEC (MIC of 32 µg/mL). These findings suggested that M-F and M5 are promising antimicrobial natural products for combating MDR K. pneumoniae and STEC nosocomial infections.

Fault Detection and Classification of CIGS Thin-Film PV Modules Using an Adaptive Neuro-Fuzzy Inference Scheme.

The use of artificial intelligence to automate PV module fault detection, diagnosis, and classification processes has gained interest for PV solar plants maintenance planning and reduction in expensive inspection and shutdown periods. The present article reports on the development of an adaptive neuro-fuzzy inference system (ANFIS) for PV fault classification based on statistical and mathematical features extracted from outdoor infrared thermography (IRT) and I-V measurements of thin-film PV modules. The selection of the membership function is shown to be essential to obtain a high classifier performance. Principal components analysis (PCA) is used to reduce the dimensions to speed up the classification process. For each type of fault, effective features that are highly correlated to the PV module's operating power ratio are identified. Evaluation of the proposed methodology, based on datasets gathered from a typical PV plant, reveals that features extraction methods based on mathematical parameters and I-V measurements provide a 100% classification accuracy. On the other hand, features extraction based on statistical factors provides 83.33% accuracy. A novel technique is proposed for developing a correlation matrix between the PV operating power ratio and the effective features extracted online from infrared thermal images. This eliminates the need for offline I-V measurements to estimate the operating power ratio of PV modules.

Influence of Microstructure and Alloy Composition on the Machinability of α/ß Titanium Alloys.

A comparative study was conducted for the machining of two α/ß titanium alloys, namely Ti-6Al-4V (Ti64) and Ti-6Al-7Nb (Ti67), using wire electric discharge machining (WEDM). The influence of cutting speed and cutting mode on the machined surfaces in terms of surface roughness (Ra), recast layer (RL), and micro-hardness have been evaluated. Rough cut (RC) mode at a cutting speed of 50 µm/s resulted in thermal damage; Ra was equal to 5.68 ± 0.44 and 4.52 ± 0.35 µm for Ti64 and Ti67, respectively. Trim-cut mode using seven cuts (TRC-VII) at the same speed decreased the Ra to 1.02 ± 0.20 µm for Ti64 and 0.92 ± 0.10 µm for Ti67. At 100 µm/s, Ra reduced from 2.34 ± 0.28 µm to 0.88 ± 0.12 µm (Ti64), and from 1.42 ± 0.15 µm to 0.90 ± 0.08µm (Ti67) upon changing from TRC-III to TRC-VII. Furthermore, a thick recast layer of 30 ± 0.93 µm for Ti64 and 14 ± 0.68 µm for Ti67 was produced using the rough mode, while TRC-III and TRC-VII modes produced layers of 12 ± 1.31 µm and 5 ± 0.72 µm for Ti64 and Ti67, respectively. Moreover, rough cut and trim cut modes of WEDM played a significant role in promoting the surface hardness of Ti64 and Ti67. By employing the Response Surface Methodology, it was found that the machining mode followed by cutting speed and the interaction between them are the most influential parameters on surface roughness. Finally, mathematical models correlating machining parameters to surface roughness were successfully developed. The results strongly promote the trim-cut mode of WEDM as a promising machining route for two-phase titanium alloys.

Variant-specific RT-qPCR for rapid screening of B.1.617 mutations in SARS-CoV-2.

The continuous emergence of new SARS-CoV-2 variants required rapid and reliable diagnostic methods for early detection and monitoring of the spread of the virus, especially in low-resource countries where whole genome sequencing is not available. We aimed to evaluate and compare the performance of two different RT-qPCR screening assays for the detection of B.1.617 lineage mutations. A total of 85 SARS-CoV-2 positive samples were collected between 9th August and 10 September 2021 and screened by two mutation-specific RT-qPCR assays for simultaneous detection of B.1.617.1 and B.1.617.2 lineage mutations. VIASURE Variant II PCR assay identified 2 Delta variant-specific mutations (L452R, and P681 R) in 80% of tested samples, while the PKamp™ Variant Detect™ assay was only able to detect one Delta variant specific mutation (L452R) in 75% of tested samples. This is the first report to show the Delta variant as the cause of the third wave in Libya. The use of multiplex RT-qPCR assays has allowed the identification of new variants for rapid screening. However, RT-qPCR results should be confirmed by whole genome sequencing of SARS-COV-2.

Fostering EFL learners' motivation, anxiety, and self-efficacy through computer-assisted language learning- and mobile-assisted language learning-based instructions.

In the literature, a mass of studies have inspected the effects of computer-assisted language learning (CALL) and mobile-assisted language learning (MALL) on Iranian English as a Foreign Language (EFL) learners' achievement. However, the effects of CALL and MALL on psychological factors, such as motivation, anxiety, and self-efficacy, have largely remained unexplored. Thus, this study explored the effects of CALL and MALL, and face-to-face (FTF) learning environments on Iranian EFL learners' motivation, anxiety, and self-efficacy. To this aim, using a random sampling method, a total of 137 male EFL intermediate learners were selected and homogenized using the Oxford Quick Placement Test (OQPT). Based on the test scores, a total of 90 EFL learners were selected and randomly assigned to three groups, namely, CALL (n = 30), MALL (n = 30), and FTF (n = 30). Then, the participants' motivation, anxiety, and self-efficacy were gauged prior to the instructions. Afterward, they received CALL-based, MALL-based, and conventional instructions which lasted 25 1-h sessions held twice a week. At the end of the instructions, the participants' motivation, anxiety, and self-efficacy were measured again. The collected data were analyzed through a one-way MANOVA. Findings evidenced that the experimental groups' motivation, anxiety, and self-efficacy were positively affected by the CALL-based and MALL-based instructions. However, there was not a statistically significant difference between the CALL group and MALL group concerning the gains of motivation, anxiety, and self-efficacy. In light of the findings, a range of implications is suggested for relevant stakeholders.

Atomic-Scale Insights into the Lateral and Vertical Epitaxial Growth in Two-Dimensional Pd2Se3-MoS2 Heterostructures.

Two-dimensional (2D) materials form heterostructures in both the lateral and vertical directions when two different materials are interfaced, but with totally different bonding mechanisms of covalent in-plane to van der Waal's layered interactions. Understanding how the competition between lateral and vertical forces influences the epitaxial growth is important for future materials development of complex mixed layered heterostructures. Here, we use atomic-resolution annular dark-field scanning transmission electron microscopy to study the detailed atomic arrangements at mixed 2D heterostructure interfaces composed of two semiconductors with distinctly different crystal symmetry and elemental composition, Pd2Se3:MoS2, in order to understand the role of different chemical bonds on the resultant epitaxy. Pd2Se3 is grown off the step edge in bilayer MoS2, and the vertical and lateral epitaxial relationships of the Pd2Se3-MoS2 heterostructures are investigated. We find that the similarity of geometry at the interface with one metal (Pd or Mo) atoms bonded with two chalcogens (S or Se) are the crucial factors to make the atomically stitched lateral junction of 2D heterostructures. In addition, the vertical van der Waal interactions that are normally dominant in layered materials can be overcome by in-plane forces if the interfacial atomic stitching is high in quality and low in defect density. This knowledge should help guide the approaches for improving the epitaxy in mixed 2D heterostructures and seamless stitching of in-plane 2D heterostructures with various complex monolayer structures.

Highly Sensitive Self-Actuated Zinc Oxide Resonant Microcantilever Humidity Sensor.

A resonant microcantilever sensor is fabricated from a zinc oxide (ZnO) thin film, which serves as both the structural and sensing layers. An open-air spatial atomic layer deposition technique is used to deposit the ZnO layer to achieve a ∼200 nm thickness, an order of magnitude lower than the thicknesses of conventional microcantilever sensors. The reduction in the number of layers, in the cantilever dimensions, and its overall lower mass lead to an ultrahigh sensitivity, demonstrated by detection of low humidity levels. A maximum sensitivity of 23649 ppm/% RH at 5.8% RH is observed, which is several orders of magnitude larger than those reported for other resonant humidity sensors. Furthermore, the ZnO cantilever sensor is self-actuated in air, an advantageous detection mode that enables simpler and lower-power-consumption sensors.