Stoichiometrically optimized eg orbital occupancy of Ni-Co oxide catalysts for Li-air batteries.

Li-air battery (LAB) technology is making continuous progress toward its theoretical capacity, which is comparable to gasoline. However, the sluggish reaction at the cathode is still a challenge. We propose a simple strategy to optimize the surface eg occupancy by adjusting the stoichiometric ratios of transition metal-based spinel structures through a controlled hydrothermal synthesis. Three distinct stoichiometries of Ni-Co oxides were used to demonstrate the direct correlation between stoichiometry and catalytic performance. The groundsel flower-like structure having a 1 : 1.4 Ni : Co atomic ratio with high surface area, high defect density, and an abundance of Ni3+ at the surface with semi-filled eg orbitals was found to benefit the structure promoting high catalytic activities in aqueous and aprotic media. The assembled LAB cells employing this cathode demonstrate an exceptional lifespan, operating for 3460 hours and completing 173 cycles while achieving the highest discharge capacity of 13 759 mA h g-1 and low charging overpotentials. The key to this prolonged performance lies in the full reversibility of the cell, attributed to its excellent OER performance. A well-surface adsorbed, amorphous LiO2/Li2O2 discharge product is found to possess high diffusivity and ease of decomposition, contributing significantly to the enhanced longevity of the cell.

Transforming Nature's Bath Sponge into Stacking Faults-Enhanced Ag Nanorings-Decorated Catalyst for Hydrogen Evolution Reaction.

The rational design of cost-effective and efficient electrocatalysts for electrochemical water splitting is essential for green hydrogen production. Utilizing nanocatalysts with abundant active sites, high surface area, and deliberate stacking faults is a promising approach for enhancing catalytic efficiency. In this study, we report a simple strategy to synthesize a highly efficient electrocatalyst for the hydrogen evolution reaction (HER) using carbonized luffa cylindrica as a conductive N-doped carbon skeleton decorated with Ag nanorings that are activated by introducing stacking faults. The introduction of stacking faults and the resulting tensile strain into the Ag nanorings results in a significant decrease in the HER overpotential, enabling the use of Ag as an efficient HER electrocatalyst. Our findings demonstrate that manipulating the crystal properties of electrocatalysts, even for materials with intrinsically poor catalytic activity such as Ag, can result in highly efficient catalysts. Further, applying a conductive carbon backbone can lower the quantities of metal needed without compromising the HER activity. This approach opens up new avenues for designing high-performance electrocatalysts with very low metallic content, which could significantly impact the development of sustainable and cost-effective electrochemical water-splitting systems.

Comparison of cytotoxicity of Miltefosine and its niosomal form on chick embryo model.

Various drugs have been used for the treatment of leishmaniasis, but they often have adverse effects on the body's organs. In this study, we aimed to explore the effects of one type of drug, Miltefosine (MIL), and its analogue or modifier, liposomal Miltefosine (NMIL), on several fetal organs using both in silico analysis and practical tests on chicken embryos. Our in silico approach involved predicting the affinities of MIL and NMIL to critical proteins involved in leishmaniasis, including Vascular Endothelial Growth Factor A (VEGF-A), the Kinase insert domain receptor (KDR1), and apoptotic-regulator proteins (Bcl-2-associate). We then validated and supported these predictions through in vivo investigations, analyzing gene expression and pathological changes in angiogenesis and apoptotic mediators in MIL- and NMIL-treated chicken embryos. The results showed that NMIL had a more effective action towards VEGF-A and KDR1 in leishmaniasis, making it a better candidate for potential operative treatment during pregnancy than MIL alone. In vivo, studies also showed that chicken embryos under MIL treatment displayed less vascular mass and more degenerative and apoptotic changes than those treated with NMIL. These results suggest that NMIL could be a better treatment option for leishmaniasis during pregnancy.

XGB Modeling Reveals Improvement of Compressive Strength of Cement-Based Composites with Addition of HPMC and Chitosan.

This study investigates the improvement in the compressive strength of cellulose/cement-based composites. Methyl cellulose (MC), carboxymethyl cellulose (CMC), and hydroxypropyl cellulose (HPMC) are separately used as the cellulose phase with different wt%. Graphene oxide (GO) and zoledronic acid (ZOL) are used as additives for bone regeneration for various formulations. Utilizing Extreme Gradient Boosting (XGB) modeling, this research demonstrates the roles of the choice of the cellulose phase, wt% of cement phase, % gelatin, % citric acid, degradation time, and concentration of GO and ZOL in influencing compressive strength. The XGB regression model, with an R2 value of 0.99 (~1), shows the predictive power of the model. Feature importance analysis demonstrates the significance of cellulose choice and the addition of chitosan in enhancing compressive strength. The correlation heatmap reveals positive associations, emphasizing the positive influence of HPMC and CMC compared with MC and the substantial impact of chitosan and citric acid on compressive strength. The model's predictive accuracy is validated through predicted compressive strength values with experimental observations, providing insights for optimizing cellulose-reinforced cements and enabling tailored material design for enhanced mechanical performance.

Physics-informed UNets for discovering hidden elasticity in heterogeneous materials.

Soft biological tissues often have complex mechanical properties due to variation in structural components. In this paper, we develop a novel UNet-based neural network model for inversion in elasticity (El-UNet) to infer the spatial distributions of mechanical parameters from strain maps as input images, normal stress boundary conditions, and domain physics information. We show superior performance - both in terms of accuracy and computational cost - by El-UNet compared to fully-connected physics-informed neural networks in estimating unknown parameters and stress distributions for isotropic linear elasticity. We characterize different variations of El-UNet and propose a self-adaptive spatial loss weighting approach. To validate our inversion models, we performed various finite-element simulations of isotropic domains with heterogenous distributions of material parameters to generate synthetic data. El-UNet is faster and more accurate than the fully-connected physics-informed implementation in resolving the distribution of unknown fields. Among the tested models, the self-adaptive spatially weighted models had the most accurate reconstructions in equal computation times. The learned spatial weighting distribution visibly corresponded to regions that the unweighted models were resolving inaccurately. Our work demonstrates a computationally efficient inversion algorithm for elasticity imaging using convolutional neural networks and presents a potential fast framework for three-dimensional inverse elasticity problems that have proven unachievable through previously proposed methods.

A combined gas-phase dissociative ionization, dissociative electron attachment and deposition study on the potential FEBID precursor [Au(CH3)2Cl]2.

Motivated by the potential of focused-electron-beam-induced deposition (FEBID) in the fabrication of functional gold nanostructures for application in plasmonic and detector technology, we conducted a comprehensive study on [Au(CH3)2Cl]2 as a potential precursor for such depositions. Fundamental electron-induced dissociation processes were studied under single collision conditions, and the composition and morphology of FEBID deposits fabricated in an ultrahigh-vacuum (UHV) chamber were explored on different surfaces and at varied beam currents. In the gas phase, dissociative ionization was found to lead to significant carbon loss from this precursor, and about 50% of the chlorine was on average removed per dissociative ionization incident. On the other hand, in dissociative electron attachment, no chlorine was removed from the parent molecule. Contrary to these observations, FEBID in the UHV setup was found to yield a quantitative loss and desorption of the chlorine from the deposits, an effect that we attribute to electron-induced secondary and tertiary reactions in the deposition process. We find this precursor to be stable at ambient conditions and to have sufficient vapor pressure to be suitable for use in HV instruments. More importantly, in the UHV setup, FEBID with [Au(CH3)2Cl]2 yielded deposits with high gold content, ranging from 45 to 61 atom % depending on the beam current and on the cleanliness of the substrates surface.

Immune checkpoints and cancer immunotherapies: insights into newly potential receptors and ligands.

Checkpoint markers and immune checkpoint inhibitors have been increasingly identified and developed as potential immunotherapeutic targets in various human cancers. Despite valuable efforts to discover novel immune checkpoints and their ligands, the precise roles of their therapeutic functions, as well as the broad identification of their counterpart receptors, remain to be addressed. In this context, it has been suggested that various putative checkpoint receptors can be induced upon activation. In the tumor microenvironment, T cells, as crucial immune response against malignant diseases as well as other immune central effector cells, such as natural killer cells, are regulated via co-stimulatory or co-inhibitory signals from immune or tumor cells. Studies have shown that exposure of T cells to tumor antigens upregulates the expression of inhibitory checkpoint receptors, leading to T-cell dysfunction or exhaustion. Although targeting immune checkpoint regulators has shown relative clinical efficacy in some tumor types, most trials in the field of cancer immunotherapies have revealed unsatisfactory results due to de novo or adaptive resistance in cancer patients. To overcome these obstacles, combinational therapies with newly discovered inhibitory molecules or combined blockage of several checkpoints provide a rationale for further research. Moreover, precise identification of their receptors counterparts at crucial checkpoints is likely to promise effective therapies. In this review, we examine the prospects for the application of newly emerging checkpoints, such as T-cell immunoglobulin and mucin domain 3, lymphocyte activation gene-3, T-cell immunoreceptor with Ig and ITIM domains (TIGIT), V-domain Ig suppressor of T-cell activation (VISTA), new B7 family proteins, and B- and T-cell lymphocyte attenuator, in association with immunotherapy of malignancies. In addition, their clinical and biological significance is discussed, including their expression in various human cancers, along with their roles in T-cell-mediated immune responses.

Green conversion of waste PET into magnetic Ni0·4Fe2·6O4/(Fe,Ni)@carbon nanostructure for adsorption and separation of dyes from aqueous media.

A nanostructured core-shell composite (Ni0·4Fe2·6O4/(Fe,Ni)@carbon, NFC) comprising magnetic nano-cores encapsulated with graphitic shells (≈80 wt%) is prepared by facile and clean mechanochemical-molten salt processing approach using waste PET; providing a specific surface area of 201.9 m2 g-1, well-developed mesopores, and ferromagnetic behavior characterized by the coercivity value of 149 Oe. NFC is utilized as a high-performance adsorbent for the removal of organic dyes from their aqueous solutions. Moreover, the magnetic performance of NFC enables the facile collection of the exhausted adsorbent out of the purified water. Performances of NFC for the removal of crystal violet dye (CV), methyl orange (MO) and rhodamine B (Rh B) from their aqueous solutions are systematically investigated under different environmental conditions including the adsorbent dosage and dye concentration, as well as the solution pH and temperature, where an impressive CV removal capacity of 201.6-243.8 mg g-1 is recorded for a wide pH range of 2-10. Mechanism and kinetics involved in the adsorption process are investigated by studying the adsorption isotherms and thermodynamics. The dye adsorption of the nanocomposite material is confirmed to follow the pseudo-second-order kinetic model combined with the Langmuir isotherm model, exhibiting an excellent spontaneous and exothermic monolayer adsorption capacity of around 153 mg g-1 (for MO) for the fresh adsorbent and around 89 mg g-1 after three adsorption-regeneration cycles.

Carbonization of Corn Leaf Waste for Na-Ion Storage Application Using Water-Soluble Carboxymethyl Cellulose Binder.

Hard carbon materials are considered to be the most practical anode materials for sodium ion batteries because of the rich availability of their resources and potentially low cost. Here, the conversion of corn leaf biomass, a largely available agricultural waste, into carbonaceous materials for Na-ion storage application is reported. Thermal analysis investigation determines the presence of exothermic events occurring during the thermal treatment of the biomass. Accordingly, various temperatures of 400, 500, and 600 °C are selected to perform carbonization treatment trials, leading to the formation of various biocarbons. The materials obtained are characterized by a combination of methods, including X-ray diffraction, electron microscopy, surface evaluation, Raman spectroscopy, and electrochemical characterizations. The Na-ion storage performances of these materials are investigated using water-soluble carboxymethyl cellulose binder, highlighting the influence of the carbonization temperature on the electrochemical performance of biocarbons. Moreover, the influence of post-mechanochemical treatment on the Na-ion storage performance of biocarbons is studied through kinetic evaluations. It is confirmed that reducing the particle sizes and increasing the carbon purity of biocarbons and the formation of gel polymeric networks would improve the Na-ion storage capacity, as well as the pseudocapacitive contribution to the total current. At a high-current density of 500 mA g-1, a specific Na-ion storage capacity of 134 mAh g-1 is recorded on the biocarbon prepared at 600 °C, followed by ball-milling and washing treatment, exhibiting a reduced charge transfer resistance of 49 Ω and an improved Na-ion diffusion coefficient of 4.8 × 10-19 cm2 s-1. This article proposes a simple and effective technique for the preparation of low-cost biocarbons to be used as the anode of Na-ion batteries.

The potential impact of emotionally loaded stimuli on over/under-estimating neutral situations among power plant control-room operators.

BACKGROUND: Human emotions vary on a contextual basis. The significance of emotions becomes even more salient in Control Room Operators (CROs) in power plants. OBJECTIVE: This study investigated the effects of emotionally loaded pictures on over/underestimating neutral situations. METHODS: Twenty CROs voluntarily enrolled in the present study. Twenty-one blocks were considered, including ten emotionally loaded and 11 neutral blocks. The stimuli were alternatively submitted to subjects in random order. Each block comprised 13 images from the International Affective Picture System (IAPS), which were shown for 5 seconds. Subjects were required to complete the Self-Assessment Manikin (SAM) after exposure to the first and the last neutral blocks, which were identical. RESULTS: Our analyses showed significant differences between IAPS arousal and SAM1 and SAM2 arousal ratings (p SAM1&IAPS = 0.00, p SAM2&IAPS = 0.02). There was no significant relationship between the first and the second arousals, and emotionally loaded images corresponded to no significant difference in terms of valence. CONCLUSION: The findings suggested that the participants overestimated neutral situations compared with IAPS only in arousal level. Furthermore, CROs can still retain their ability to assess neutral situations in the case of viewing emotional stimuli, especially in valence level, at least half an hour after the first rating. A study design with pure negative/positive and high arousal levels may still provide even more significant results.

A systematic review on machine learning and deep learning techniques in the effective diagnosis of Alzheimer's disease.

Alzheimer's disease (AD) is a brain-related disease in which the condition of the patient gets worse with time. AD is not a curable disease by any medication. It is impossible to halt the death of brain cells, but with the help of medication, the effects of AD can be delayed. As not all MCI patients will suffer from AD, it is required to accurately diagnose whether a mild cognitive impaired (MCI) patient will convert to AD (namely MCI converter MCI-C) or not (namely MCI non-converter MCI-NC), during early diagnosis. There are two modalities, positron emission tomography (PET) and magnetic resonance image (MRI), used by a physician for the diagnosis of Alzheimer's disease. Machine learning and deep learning perform exceptionally well in the field of computer vision where there is a requirement to extract information from high-dimensional data. Researchers use deep learning models in the field of medicine for diagnosis, prognosis, and even to predict the future health of the patient under medication. This study is a systematic review of publications using machine learning and deep learning methods for early classification of normal cognitive (NC) and Alzheimer's disease (AD).This study is an effort to provide the details of the two most commonly used modalities PET and MRI for the identification of AD, and to evaluate the performance of both modalities while working with different classifiers.

Sleep Micro-Macro-structures in Psychophysiological Insomnia. PSG Study.

Study Objectives: To address sleep micro-macro-structures in psychophysiological insomnia (PPI) as denoted by cyclic alternating pattern (CAP), Sleep spindles, and hyperarousal as microstructures and sleep characteristics such as sleep stages' variables, and heart rate as macrostructures. Methods: Two statistical populations, with 20 participants in each, are addressed: good sleepers (GS) and patients with psychophysiological insomnia (PPI). The sleep polysomnography (PSG) for one night was performed and sleep macro-micro-structures extraction was implemented for each participant. Cyclic alternating patterns were scored manually and other structures were monitored by the original PSG's device software. Analytical methods are used to dissect the results. Result: The findings imply: (a) psychophysiological insomnia is characterized by CAP differences from good sleepers which are associated with hyperarousal; (b) Regarding microstructure, more microarousals in sleep stages caused more number of wake index. (c) The ratio of sleep stages, sleep latency and heart rate as sleep macrostructure are significantly changed. (d) There is no significant difference between PPI and GS groups on spindles length in our research. Conclusion: Regarding all sleep disorders and especially PPI, CAP variables, EEG arousals, and sleep spindles as microstructures and Total Sleep Time, Sleep Latency, number of waking, REM duration, and Heart Rate as macrostructures were found to be critical for the diagnosis of psychophysiological insomnia The analysis contributes to understanding better approaches in the quantitative specification of psychophysiological insomnia compare to good sleepers.

Ultrasound, photoacoustic, and magnetic resonance imaging to study hyperacute pathophysiology of traumatic and vascular brain injury.

BACKGROUND AND PURPOSE: Cerebrovascular dynamics and pathomechanisms that evolve in the minutes and hours following traumatic vascular injury in the brain remain largely unknown. We investigated the pathophysiology evolution in mice within the first 3 hours after closed-head traumatic brain injury (TBI) and subarachnoid hemorrhage (SAH), two significant traumatic vascular injuries. METHODS: We took a multimodal imaging approach using photoacoustic imaging, color Doppler ultrasound, and MRI to track injury outcomes using a variety of metrics. RESULTS: Brain oxygenation and velocity-weighted volume of blood flow (VVF) values significantly decreased from baseline to 15 minutes after both TBI and SAH. TBI resulted in 19.2% and 41.0% ipsilateral oxygenation and VVF reductions 15 minutes postinjury, while SAH resulted in 43.9% and 85.0% ipsilateral oxygenation and VVF reduction (p < .001). We found partial recovery of oxygenation from 15 minutes to 3 hours after injury for TBI but not SAH. Hemorrhage, edema, reduced perfusion, and altered diffusivity were evident from MRI scans acquired 90-150 minutes after injury in both injury models, although the spatial distribution was mostly focal for TBI and diffuse for SAH. CONCLUSIONS: The results reveal that the cerebral oxygenation deficits immediately following injuries are reversible for TBI and irreversible for SAH. Our findings can inform future studies on mitigating these early responses to improve long-term recovery.

Sustainable regeneration of high-performance LiCoO2 from completely failed lithium-ion batteries.

Utilising the solid-state synthesis method is an easy and effective way to recycle spent lithium-ion batteries. However, verifying its direct repair effects on completely exhausting cathode materials is necessary. In this work, the optimal conditions for direct repair of completely failed cathode materials by solid-state synthesis are explored. The discharge capacity of spent LiCoO2 cathode material is recovered from 21.7 mAh g-1 to 138.9 mAh g-1 under the optimal regeneration conditions of 850 °C and n(Li)/n(Co) ratio of 1:1. The regenerated materials show excellent electrochemical performance, even greater than the commercial LiCoO2. In addition, based on the whole closed-loop recycling process, the economic and environmental effects of various recycling techniques and raw materials used in the battery production process are assessed, confirming the superior economic and environmental feasibility of direct regeneration method.

Surface Modification of Transition Metal Dichalcogenide Nanosheets for Intrinsically Self-Healing Hydrogels with Enhanced Mechanical Properties.

Nanocomposites with enhanced mechanical properties and efficient self-healing characteristics can change how the artificially engineered materials' life cycle is perceived. Improved adhesion of nanomaterials with the host matrix can drastically improve the structural properties and confer the material with repeatable bonding/debonding capabilities. In this work, exfoliated 2H-WS2 nanosheets are modified using an organic thiol to impart hydrogen bonding sites on the otherwise inert nanosheets by surface functionalization. These modified nanosheets are incorporated within the PVA hydrogel matrix and analyzed for their contribution to the composite's intrinsic self-healing and mechanical strength. The resulting hydrogel forms a highly flexible macrostructure with an impressive enhancement in mechanical properties and a very high autonomous healing efficiency of 89.92%. Interesting changes in the surface properties after functionalization show that such modification is highly suitable for water-based polymeric systems. Probing into the healing mechanism using advanced spectroscopic techniques reveals the formation of a stable cyclic structure on the surface of nanosheets, mainly responsible for the improved healing response. This work opens an avenue toward the development of self-healing nanocomposites where chemically inert nanoparticles participate in the healing network rather than just mechanically reinforcing the matrix by slender adhesion.

A dual-mode neurostimulation approach to enhance athletic performance outcome in experienced taekwondo practitioners.

Transcranial Direct Current Stimulation (tDCS) is a growing empirical approach to improve athletic performance. Some recent studies have investigated the effects of transcutaneous spinal direct current stimulation (tsDCS) on the motor performance such as reaction time. TDCS and tsDCS can lead to alteration of the spontaneous neural activity, and the membrane potentials of motor neurons in cerebral cortex and spinal interneurons, respectively. Given the paucity of experimental studies on the non-invasive brain stimulation in the field of sports neuroscience, especially martial sports, the present study aimed at investigating the effects of neurostimulation in potentiating the motor and cognitive functions in experienced taekwondo practitioners. The study sample included 15 experienced male taekwondo players who received real or sham direct current stimulation on the primary motor cortex (M1) and the lumbar spinal segment (T12-L2) over two sessions, 72 h apart. Next, the performance of the participants was evaluated through a simulation of taekwondo exercise directly after the sham and real sessions. Moreover, a cognitive platform (CBS: Cambridge Brain Science) was used to investigate the participants' cognitive profile in each instance. Unlike sham stimulation, real tDCS was associated with improved selective attention and reaction time in both in the simulated task performance and cognitive examination. The concurrent cortical and trans-spinal tDCS was found to improve selective attention (31% performance improvement) (P < 0.0001) [EFFECT SIZE; 1.84]. and reduce reaction time (4.7% performance improvement) (P < 0.0001) [EFFECT SIZE; 0.02]. Meanwhile, the intervention failed to leave a significant change in cognitive functions evaluated through CBS (P > 0.05). As informed by our results, the present dual-mode neurostimulation could improve motor functions potentially through the effect of tsDCS over the spinal interneurons and tDCS over the primary motor cortex. Likewise, our findings suggested an improved performance in simulated taekwondo task after real- but not sham-stimulation. This study paves the way for designing neurostimulation protocols to improve the performance of professional athletes, namely martial art practitioners, including their accuracy and velocity of reactions. Such positive effects of neuostimulation in athletic performance as demonstrated in this research and similar reports are expected to enhance the athletes' success in professional competitions.

Elasticity imaging using physics-informed neural networks: Spatial discovery of elastic modulus and Poisson's ratio.

Elasticity imaging is a technique that discovers the spatial distribution of mechanical properties of tissue using deformation and force measurements under various loading conditions. Given the complexity of this discovery, most existing methods approximate only one material parameter while assuming homogeneous distributions for the others. We employ physics-informed neural networks (PINN) in linear elasticity problems to discover the space-dependent distribution of both elastic modulus (E) and Poisson's ratio (ν) simultaneously, using strain data, normal stress boundary conditions, and the governing physics. We validated our model on three examples. First, we experimentally loaded hydrogel samples with embedded stiff inclusions, representing tumorous tissue, and compared the approximations against ground truth determined through tensile tests. Next, using data from finite element simulation of a rectangular domain containing a stiff circular inclusion, the PINN model accurately localized the inclusion and estimated both E and ν. We observed that in a heterogeneous domain, assuming a homogeneous ν distribution increases estimation error for stiffness as well as the area of the stiff inclusion, which could have clinical importance when determining size and stiffness of tumorous tissue. Finally, our model accurately captured spatial distribution of mechanical properties and the tissue interfaces on data from another computational model, simulating uniaxial loading of a rectangular hydrogel sample containing a human brain slice with distinct gray matter and white matter regions and complex geometrical features. This elasticity imaging implementation has the potential to be used in clinical imaging scenarios to reliably discover the spatial distribution of mechanical parameters and identify material interfaces such as tumors. STATEMENT OF SIGNIFICANCE: Our work is the first implementation of physics-informed neural networks to reconstruct both material parameters - Young's modulus and Poisson's ratio - and stress distributions for isotropic linear elastic materials by having deformation and force measurements. We comprehensively validate our model using experimental measurements and synthetic data generated using finite element modeling. Our method can be implemented in clinical elasticity imaging scenarios to improve diagnosis of tumors and for mechanical characterization of biomaterials and biological tissues in a minimally invasive manner.

Process and outcome evaluation of directly observed treatment short course (DOTs) in Kerman city, Southeast of Iran.

BACKGROUND: Understanding tuberculosis (TB) treatment programs' process and the outcome is one of the critical strategies to prevent the disease's occurrence and accelerate achieving sustainable development goals to reduce TB cases. The present study aimed to evaluate directly observed treatment short-course (DOTs) for tuberculosis. METHODS: The present cross-sectional, descriptive-analytical study extracted information from the tuberculosis surveillance system's recorded data by a researcher-made checklist with questions from patients and health system staff. We analyzed the data by SPSS version 20. RESULTS: The outcome of patients' treatment was 85.39% improved, and the rest were death and failure of treatment and absence from treatment. The mean and standard deviation of the onset of the first symptom and diagnosis and detection of the disease was 117 and 126 days, respectively. The mean and standard deviation of the interval between diagnosis and treatment was 5.53 and 8.03 days, respectively. Regarding the treatment length, 95.5% of the cases followed the treatment length, and the rest were not observed. The history of hospitalization was 45.3% among patients, and the rest had no history of hospitalization, and the mean and standard deviation of the day of hospitalization were 6.68 ± 9.50 days. CONCLUSIONS: The existence of an appropriate program for early diagnosis of tuberculosis, observing the length of treatment, training private and public centers to strengthen the care system, and strengthening the DOTs program to control tuberculosis seems to be necessary.

On the Electron-Induced Reactions of (CH3)AuP(CH3)3: A Combined UHV Surface Science and Gas-Phase Study.

Focused-electron-beam-induced deposition (FEBID) is a powerful nanopatterning technique where electrons trigger the local dissociation of precursor molecules, leaving a deposit of non-volatile dissociation products. The fabrication of high-purity gold deposits via FEBID has significant potential to expand the scope of this method. For this, gold precursors that are stable under ambient conditions but fragment selectively under electron exposure are essential. Here, we investigated the potential gold precursor (CH3)AuP(CH3)3 using FEBID under ultra-high vacuum (UHV) and spectroscopic characterization of the corresponding metal-containing deposits. For a detailed insight into electron-induced fragmentation, the deposit's composition was compared with the fragmentation pathways of this compound through dissociative ionization (DI) under single-collision conditions using quantum chemical calculations to aid the interpretation of these data. Further comparison was made with a previous high-vacuum (HV) FEBID study of this precursor. The average loss of about 2 carbon and 0.8 phosphor per incident was found in DI, which agreed well with the carbon content of the UHV FEBID deposits. However, the UHV deposits were found to be as good as free of phosphor, indicating that the trimethyl phosphate is a good leaving group. Differently, the HV FEBID experiments showed significant phosphor content in the deposits.