Green hematite depression for reverse selective flotation separation from quartz by locust bean gum.

Reverse cationic flotation is currently the main processing technique for upgrading fine hematite from silicates. Flotation is known as an efficient method of mineral enrichment that deals with possibly hazardous chemicals. Thus, using eco-friendly flotation reagents for such a process is an emerging need for sustainable development and green transition. As an innovative approach, this investigation explored the potential of locust bean gum (LBG) as a biodegradable depressant for the selective separation of fine hematite from quartz through reverse cationic flotation. Various flotation conditions (micro and batch flotation) were conducted, and the mechanisms of LBG adsorption have been examined by different analyses (contact angle measurement, surface adsorption, zeta potential measurements, and FT-IR analysis). The micro flotation outcome indicated that the LBG could selectively depress hematite particles with negligible effect on quartz floatability. Flotation of mixed minerals (hematite and quartz mixture in various ratios) indicated that LGB could enhance separation efficiency (hematite recovery > 88%). Outcomes of the surface wettability indicated that even in the presence of the collector (dodecylamine), LBG decreased the hematite work of adhesion and had a slight effect on quartz. The LBG adsorbed selectively by hydrogen bonding on the surface of hematite based on various surface analyses.

Radiomics Outperforms Clinical and Radiologic Signs in Predicting Spontaneous Basal Ganglia Hematoma Expansion: A Pilot Study.

Prediction of the hematoma expansion (HE) of spontaneous basal ganglia hematoma (SBH) from the first non-contrast CT can result in better management, which has the potential of improving outcomes. This study has been designed to compare the performance of "Radiomics analysis," "radiology signs," and "clinical-laboratory data" for this task. We retrospectively reviewed the electronic medical records for clinical, demographic, and laboratory data in patients with SBH. CT images were reviewed for the presence of radiologic signs, including black-hole, blend, swirl, satellite, and island signs. Radiomic features from the SBH on the first brain CT were extracted, and the most predictive features were selected. Different machine learning models were developed based on clinical, laboratory, and radiology signs and selected Radiomic features to predict hematoma expansion (HE). The dataset used for this analysis included 116 patients with SBH. Among different models and different thresholds to define hematoma expansion (10%, 20%, 25%, 33%, 40%, and 50% volume enlargement thresholds), the Random Forest based on 10 selected Radiomic features achieved the best performance (for 25% hematoma enlargement) with an area under the curve (AUC) of 0.9 on the training dataset and 0.89 on the test dataset. The models based on clinical-laboratory and radiology signs had low performance (AUCs about 0.5-0.6).

An environmentally friendly method for extraction of cobalt and molybdenum from spent catalysts using deep eutectic solvents (DESs).

There has been a substantially increasing demand for energy critical elements (ECEs) in recent years as energy-related technology has advanced rapidly. Spent catalysts are known as potential sources of ECCs such as Ni, Co, Mo, W, V, and rare earth elements. This study developed a novel environmentally friendly process for recovering cobalt and molybdenum from spent hydroprocessing catalysts using deep eutectic solvents (DESs). DESs based on p-toluenesulfonic acid achieved high metal extraction at 100 °C and a pulp density of 20 g/L for 48 h which 93% of cobalt and 87% of molybdenum were dissolved. FT-IR and H-NMR analyses were conducted to determine whether hydrogen bonds form between p-toluenesulfonic acid-based DES components. Leaching kinetic models were also developed for DES systems. The experimental results were well-matched with the shrinking core models. The leaching controlling step of DES-1 was determined to be the diffusion through the product layer based on kinetic studies, with an activation energy of 22.56 kJ/mol for Co and 29.34 kJ/mol for Mo in DES-1. Similarly, the mixed control reaction with an activation energy of 38.09 kJ/mol for Co and 31.48 kJ/mol for Mo in DES-2 was found to control the leaching kinetic mechanism of the DES-2 sample.

Selection of reference genes for RT-qPCR analysis of rice with Rhizoctonia solani infection and biocontrol PGPR/KSi application.

BACKGROUND: Rhizoctonia solani (AG1 IA) is an important pathogen of rice (Oryza sativa L.) that causes rice sheath blight (RSB). Since control of RSB by breeding and fungicides have had limited success, novel strategies like biocontrol with plant growth-promoting rhizobacteria (PGPR) can be an effective alternative. METHOD AND RESULTS: Seven commonly used reference genes (RGs), 18SrRNA, ACT1, GAPDH2, UBC5, RPS27, eIF4a and CYP28, were evaluated for their stability in rice-R. solani-PGPR interaction for real-time quantitative PCR (RT-qPCR) analysis. Different algorithms were examined, Delta Ct, geNorm, NormFinder, BestKeeper, and comprehensive ranking by RefFinder, to evaluate RT-qPCR of rice in tissues infected with R. solani and treated with the PGPR strains, Pseudomonas saponiphilia and Pseudomonas protegens, with potassium silicate (KSi) alone or in combination with each PGPR strain. RG stability was affected for each treatment and treatment-specific RG selection was suggested. Validation analysis was done for nonexpressor of PR-1(NPR1) for each treatment. CONCLUSION: Overall, ACT1 was the most stable RG with R. solani infection alone, GAPDH2 with R. solani infection plus KSi, UBC5 with R. solani infection plus P. saponiphilia, and eIF4a with R. solani infection plus P. protegens. Both ACT1 and RPS27 were the most stable with the combination of KSi and P. saponiphilia, while RPS27 was the most stable with the combination of KSi and P. protegens.

CSF-Targeted Proteomics Indicate Amyloid-Beta Ratios in Patients with Alzheimer's Dementia Spectrum.

Background: According to recent studies, amyloid-ß (Aß) isoforms as cerebrospinal fluid (CSF) biomarkers have remarkable predictive value for cognitive decline in the early stages of Alzheimer's disease (AD). Herein, we aimed to investigate the correlations between several targeted proteomics in CSF samples with Aß ratios and cognitive scores in patients in AD spectrum to search for potential early diagnostic utility. Methods: A total of 719 participants were found eligible for inclusion. Patients were then categorized into cognitively normal (CN), mild cognitive impairment (MCI), and AD and underwent an assessment of Aß and proteomics. Clinical Dementia Rating (CDR), Alzheimer's Disease Assessment Scale (ADAS), and Mini Mental State Exam (MMSE) were used for further cognitive assessment. The Aß42, Aß42/Aß40, and Aß42/38 ratios were considered as means of comparison to identify those peptides corresponding significantly to these established biomarkers and cognitive scores. The diagnostic utility of the IASNTQSR, VAELEDEK, VVSSIEQK, GDSVVYGLR, EPVAGDAVPGPK, and QETLPSK was assessed. Results: All investigated peptides corresponded significantly to Aß42 in controls. In those with MCI, VAELEDEK and EPVAGDAVPGPK were significantly correlated with Aß42 (p value < 0.001). Additionally, IASNTQSR, VVSSIEQK, GDSVVYGLR, and QETLPSK were significantly correlated with Aß42/Aß40 and Aß42/38 (p value < 0.001) in this group. This group of peptides similarly corresponded to Aß ratios in those with AD. Eventually, IASNTQSR, VAELEDEK, and VVSSIEQK were significantly associated with CDR, ADAS-11, and ADAS-13, particularly in MCI group. Conclusion: Our research suggests potential early diagnostic and prognostic utilities for certain peptides extracted from CSF-targeted proteomics research. The ethical approval of ADNI is available at ClinicalTrials.gov with Identifier: NCT00106899.

Incorporation of Saqez essential oil into polyvinyl alcohol/chitosan bilayer hydrogel as a potent wound dressing material.

Nowadays, many studies are conducted on multilayer hydrogels for wound dressing. On the other hand, considering the emergence of bacterial resistance to common antibiotics, studies on the use of natural essential oils and their derivatives that have antibacterial and antioxidant activity can be useful. Herein, a novel bilayer hydrogel developed from polyvinyl alcohol and chitosan with the incorporation of Saqez essential oil (SEO) was synthesized. The results showed a gel-type structure with specific compression and flexibility, while the microscopic images confirmed the formation of a bilayer hydrogel. Further, the data showed that increasing the concentration of SEO reduces the swelling and water vapor permeability and increases the water retention and hydrophobicity of the hydrogel surface. The effects of the combination of SEO in the bilayer hydrogel led to a strong antioxidant property and increased antimicrobial activity. Also, the in vitro results demonstrated that the bilayer hydrogels are biocompatible, non-toxic, and blood compatible. Finally, the results of the in vivo tests showed that these bilayer hydrogels had good homeostatic efficiency. Overall, the obtained results indicate that these bilayer hydrogels are promising candidates for wound dressing.

Radiomics for differentiation of the posterior fossa pilocytic astrocytoma versus hemangioblastomas in adults. A pilot study.

PURPOSE: Both pilocytic astrocytoma (PA) and hemangioblastoma (HB) are common primary neoplasms of the posterior fossa with similar radiological manifestations. This study was conducted to evaluate the role of Radiomics in differentiating these two conditions in adults. MATERIALS AND METHODS: After a retrospective search of our institutional imaging archive, adult patients with a known diagnosis of PA or HB were included. We reviewed each patient's most recent preoperative brain magnetic resonance imaging (MRI). The solid enhancing nodule of each lesion on post-contrast T1 sequence was manually segmented. Multiple Radiomics features were then extracted from each nodule using the Pyradiomics library. Subsequently, the most predictive features were identified by feature selection models. Following this, different machine learning (ML) models were constructed based on these selected features to classify lesions as PA or HB. Finally, we evaluated the performance of each model by leave-one-out cross-validation. RESULTS: With inclusion and exclusion criteria, 34 enhancing PA nodules and 39 HB nodules were selected. A total of 115 features were extracted from each enhancing nodule. Twelve characteristics were detected as most predictive of histopathological diagnosis. Among various ML models, the neural network had the best performance in differentiating these two conditions with an AUC of 0.9 and an accuracy of 82%. CONCLUSIONS: In this retrospective study, Radiomics MRI techniques demonstrated high performance in distinguishing adult posterior fossa PA from HB. Future development of Radiomics models may advance presurgical diagnosis of these two conditions when added to routine clinical practice and thus improve patient management.

Higher dietary total antioxidant capacity (TAC) reduces the risk of cardio-metabolic risk factors among adults: An updated systematic review and meta-analysis.

Background: Numerous studies have revealed the protective role of dietary antioxidants against hypertension and diabetes. In the current systematic review and meta-analysis, we evaluated the possible role of dietary total antioxidant capacity (TAC) against metabolic parameters in the adult population. Methods: A literature search of authentic electronic resources including PubMed, Scopus, Web of Sciences, and Cochrane had been performed to retrieve the qualified observational studies that reported the mean plus/minus the SD for the parameter in subjects of the highest versus lowest dietary TAC categories up to July 2020. Results: Totally, the number of included studies was 13 for fasting blood sugar (FBS), 12 for systolic blood pressure (SBP), and 12 for diastolic blood pressure (DBP), with the participants' number of 26349. The results of the current study showed that being at highest category of TAC significantly reduces serum FBS (WMD: -2.381; CI: -3.445, -1.316; P<0.001), SBP (WMD: -1.080; CI: -1.458, -0.701; P<0.001) and DBP (WMD: -0.854; CI: -1.655, -0.052; P<0.001), while no significant difference in the serum insulin, HOMA-IR values, prevalence of type 2 diabetes (T2DM) (P=0.37) and hypertension (HTN) (P=0.09) was observed. Subgroup analysis revealed the geographical location, dietary assessment tool, sample size, and gender as possible sources of heterogeneity. Conclusion: Higher intake of dietary TAC was associated with reduced SBP, DBP, and FBS in the current observational studies of this meta-analysis. These findings further confirm the clinical importance of dietary antioxidants in the prevention of different metabolic disorders.

The Assessment of Marcaine Versus Meperidine for Spinal Anesthesia in Anorectal Surgery: A Randomized Clinical Trial.

Background: Spinal anesthesia (SA) for the surgical management of chronic anal fissures is favored by surgeons as it provides an early return to daily activities; however, the agents applied for SA to achieve the best outcomes with minimized adverse effects are a matter of debate. Objectives: This study aimed to assess the utility of Marcaine versus meperidine for SA induction of anoderm surgery. Methods: This randomized clinical trial (RCT) was conducted on 138 patients with chronic anal fissures who were candidates for surgical management in 2020. The patients were randomly assigned to two groups of SA using 2.5 mL of hyperbaric Marcaine 0.5% (n = 69) or 1 mg/kg of meperidine (n = 69). Pain severity (measured via Numerical Rating Scale (NRS)), anal sphincter tone manometry (measured at baseline and the end of the sphincterotomy), and drug-related adverse effects were compared between the groups. Results: Both agents led to significant pain relief within 24 hours after SA (P < 0.05); nevertheless, pain severity was remarkably lower in meperidine-treated patients in different measurements performed during the first 24 hours after SA (P < 0.05). The sphincteric tone significantly decreased in both groups (P < 0.001), while the postoperative tone was significantly less in the Marcaine-treated patients (65.22 ± 3.02 versus 46.04 ± 1.97, P < 0.001). The two groups did not differ regarding the adverse effects (P > 0.05). Conclusions: Meperidine for SA in anal fissure surgical management was relatively superior to Marcaine, as postoperative pain control was remarkably better achieved with meperidine. However, anal sphincter tone reached a normal range in Marcaine-treated cases, and the average tone in those anesthetized with meperidine was slightly above the normal limits.

Evaluation of the epidemiologic, clinical, radiologic, and treatment methods of patients with subacute and chronic meningitis.

BACKGROUND: Meningitis is known as a meningeal inflammation accompanied by pleocytosis in the cerebrospinal fluid (CSF), and can be classified into acute, subacute, and chronic meningitis based on symptoms duration of ≤ 5 days, ≥ 5 days and ≥ 4 weeks, respectively. Subacute and chronic meningitis are caused mainly by indolent infectious agents and noninfectious causes such as autoimmune, and neoplastic. In this study, we investigated the characteristics, diagnosis, and treatment of subacute and chronic meningitis. METHODS: We extracted the medical records of patients with chronic and subacute meningitis who were referred to three tertiary centers from Jun 2011 to Jun 2021. Initially, 2050 cases of meningitis were screened, and then 79 patients were included in the study. RESULTS: Headache (87.3%), nausea and vomiting (74.7%), fever (56.4%), and visual impairments (55.7%) were the most prevalent symptoms. The most common signs were nuchal rigidity (45.3%), altered mental status (26.9%), and papillary edema (37.5%). Brain computed tomography (CT) was normal in 68.6% of the patients while 22.9% of the cases had hydrocephalus. Brain magnetic resonance imaging (MRI) was normal in 60.0% of the patients. The most common abnormal MRI findings were leptomeningeal enhancement (16.0%) and hydrocephalus (16.0%). We had a 44.3% definite diagnosis with bacterial (n:25, 31.6%) and neoplastic (n:8, 10.1%) being the most prevalent etiologies. Mycobacterium tuberculosis (60%) and Brucella spp. (12%) were the most prevalent bacterial pathogens. CONCLUSIONS: The most common etiologies include infectious, neoplastic, and immunologic. Due to insidious presentation and uncommon etiologies, establishing a proper diagnosis, and providing timely targeted treatment for patients with subacute and chronic meningitis remains a challenge for clinicians.

Synthesis and study of CuNiTiO3 as an ORR electrocatalyst to enhance microbial fuel cell efficiency.

Microbial fuel cells (MFCs) have the capability of simultaneous sewage treatment and electricity generation. Modifying the cathode electrode enhances their efficiency. In this study, NiTiO3 and CuNiTiO3 were synthesized for practical application as cathode catalysts in a dual-chamber MFC and the performance of the modified cathodes was evaluated against a bare graphite electrode. SEM images showed that the particle sizes were mostly in the range of 40-120 and 20-80 nm for NiTiO3 and CuNiTiO3, respectively. According to AFM results, CuNiTiO3 presented a higher surface roughness than NiTiO3. MFC using CuNiTiO3/G electrode with a reduction potential value of -0.27 V (vs. SCE) and a power density of 62.18 mW m-2 showed better oxygen reduction reaction (ORR) activity compared with NiTiO3/G and the bare graphite. MFC using CuNiTiO3 cathode also showed the highest values in terms of chemical oxygen demand (COD) removal (75%) and the calculated coulombic efficiency (CE, 10%). The results obtained in this study, introduce CuNiTiO3 as a promising electrocatalyst for further improvement of the cathodic reactions in MFC applications.

Green extraction of nickel and valuable metals from pyrrhotite samples with different crystallographic structures through acidophilic bioleaching.

Nowadays, due to the strategic status of nickel in the global market, utilizing its disregarded resources like low-grade nickel containing pyrrhotite is of significant importance. A comprehensive set of experiments and analyses were performed to determine the bioleaching capability and mechanism for nickel extraction from hexagonal and monoclinic pyrrhotite. Over 95% Ni extraction was achieved from the hexagonal pyrrhotite sample. Ni extraction from the monoclinic sample reached its maximum value of 67% and 90% at 3% pulp density, with mixed mesophilic and moderately thermophilic cultures, respectively. Characterization analyses indicated that jarosite and elemental sulfur formation in mixed mesophilic bioleaching reduced the samples' bio-oxidation rate and metal dissolution. The kinetics study revealed that the controlling step in thermophilic bioleaching is the chemical reaction; however, the mixed control model was best fitted on mesophilic data. Electrochemistry studies confirmed bioleaching results and indicated that monoclinic pyrrhotite's oxidation rate under the operating conditions is faster than hexagonal pyrrhotite, and the temperature positively correlates with the oxidation rate. Toxicity assessment analysis showed that the final residues of both bioleached samples could be considered environmentally safe.

Discovery of Leptulipin, a New Anticancer Protein from theIranian Scorpion, Hemiscorpius lepturus.

Cancer is one of the leading causes of mortality in the world. Unfortunately, the present anticancer chemotherapeutics display high cytotoxicity. Accordingly, the discovery of new anticancer agents with lower side effects is highly necessitated. This study aimed to discover an anticancer compound from Hemiscorpius lepturus scorpion venom. Bioactivity-guided chromatography was performed to isolate an active compound against colon and breast cancer cell lines. 2D electrophoresis and MALDI-TOF were performed to identify the molecule. A partial protein sequence was obtained by mass spectrometry, while the full-length was deciphered using a cDNA library of the venom gland by bioinformatics analyses and was designated as leptulipin. The gene was cloned in pET-26b, expressed, and purified. The anticancer effect and mechanism action of leptulipin were evaluated by MTT, apoptosis, and cell cycle assays, as well as by gene expression analysis of apoptosis-related genes. The treated cells displayed inhibition of cell proliferation, altered morphology, DNA fragmentation, and cell cycle arrest. Furthermore, the treated cells showed a decrease in BCL-2 expression and an increase in Bax and Caspase 9 genes. In this study, we discovered a new anticancer protein from H. lepturus scorpion venom. Leptulipin showed significant anticancer activity against breast and colon cancer cell lines.

A cleaner approach for high-efficiency regeneration of base and precious metals from waste printed circuit boards through stepwise oxido-acidic and thiocyanate leaching.

This work evaluated a green route for developing an eco-friendly flowsheet to regenerate base and precious metals from waste printed circuits boards (WPCBs). Copper (as nanoparticles with an average diameter of 50 nm) and other base metals were extracted via oxidative acid leaching with high efficiency. Thiocyanate was employed for the first time as a green and economical reagent for the extraction of gold from pretreated WPCB. The effect of various parameters, including reagent dosage and temperature, was evaluated on the gold leaching rate, and 100% gold dissolution was achieved at the optimal condition. It was found that ferric iron concentration as the gold leaching oxidant has a notable effect on gold extraction. Also, at temperatures above room temperature, the recovery rate increases in a short period and then decreases continuously. The activation energy of the optimum gold thiocyanate leaching was found to be 42.84 kJ/mol, indicating chemical reaction to be the rate-controlling step. Gold extraction from the thiocyanate medium was carried out by employing activated carbon, where 100% gold adsorption was achieved in 2 h. Toxicity assessment of final residue revealed that it could be categorized as an environmentally safe waste with negligible risk.

Artemisinins in Combating Viral Infections Like SARS-CoV-2, Inflammation and Cancers and Options to Meet Increased Global Demand.

Artemisinin is a natural bioactive sesquiterpene lactone containing an unusual endoperoxide 1, 2, 4-trioxane ring. It is derived from the herbal medicinal plant Artemisia annua and is best known for its use in treatment of malaria. However, recent studies also indicate the potential for artemisinin and related compounds, commonly referred to as artemisinins, in combating viral infections, inflammation and certain cancers. Moreover, the different potential modes of action of artemisinins make these compounds also potentially relevant to the challenges the world faces in the COVID-19 pandemic. Initial studies indicate positive effects of artemisinin or Artemisia spp. extracts to combat SARS-CoV-2 infection or COVID-19 related symptoms and WHO-supervised clinical studies on the potential of artemisinins to combat COVID-19 are now in progress. However, implementing multiple potential new uses of artemisinins will require effective solutions to boost production, either by enhancing synthesis in A. annua itself or through biotechnological engineering in alternative biosynthesis platforms. Because of this renewed interest in artemisinin and its derivatives, here we review its modes of action, its potential application in different diseases including COVID-19, its biosynthesis and future options to boost production.

Clinical applications of diffusion-weighted sequence in brain imaging: beyond stroke.

Diffusion-weighted imaging (DWI) is a well-established MRI sequence for diagnosing early stroke and provides therapeutic implications. However, DWI yields pertinent information in various other brain pathologies and helps establish a specific diagnosis and management of other central nervous system disorders. Some of these conditions can present with acute changes in neurological status and mimic stroke. This review will focus briefly on diffusion imaging techniques, followed by a more comprehensive description of the utility of DWI in common neurological entities beyond stroke.

The Role of Machine Learning and Radiomics for Treatment Response Prediction in Idiopathic Normal Pressure Hydrocephalus.

Introduction Ventricular shunting remains the standard of care for patients with idiopathic normal pressure hydrocephalus (iNPH); however, not all patients benefit from the shunting. Prediction of response in advance can result in improved patient selection for ventricular shunting. This study aims to develop a machine learning predictive model for treatment response after shunt placement using the clinical and radiomics features. Methods In this retrospective pilot study, the medical records of iNPH patients who underwent ventricular shunting were evaluated. In each patient, the "idiopathic normal pressure hydrocephalus grading scale" (iNPHGS) and a "Modified Rankin Scale" were calculated before and after surgery. The subsequent treatment response was calculated as the difference between the iNPHGS scores before and after surgery. iNPHGS score reduction of two or more than two were considered as treatment response. The presurgical MRI scans were evaluated by radiologists, the ventricular systems were segmented on the T2-weighted images, and the radiomics features were extracted from the segmented ventricular system. Using Orange data mining open-source platform, different machine learning models were then developed based on the presurgical clinical features and the selected radiomics features to predict treatment response after shunt placement. Results After the implementation of the inclusion criteria, 78 patients were included in this study. One hundred twenty radiomics features were extracted, and the 12 best predictive radiomics features were selected. Using only clinical data (iNPHGS and Modified Rankin Scale), the random forest model achieved the best performance in treatment prediction with an area under the curve (AUC) of 0.71. Adding the Radiomics analysis to the clinical data improved the prediction performance, with the support vector machine (SVM) achieving the highest rank in treatment prediction with an AUC of 0.8. Adding age and sex to the analysis did not improve the prediction. Conclusion Using machine learning models for treatment response prediction in patients with iNPH is feasible with acceptable accuracy. Adding the Radiomics analysis to the clinical features can further improve the predictive performance. SVM is likely the best model for this task.

Simulation and Modeling of Novel Electronic Device Architectures with NESS (Nano-Electronic Simulation Software): A Modular Nano TCAD Simulation Framework.

The modeling of nano-electronic devices is a cost-effective approach for optimizing the semiconductor device performance and for guiding the fabrication technology. In this paper, we present the capabilities of the new flexible multi-scale nano TCAD simulation software called Nano-Electronic Simulation Software (NESS). NESS is designed to study the charge transport in contemporary and novel ultra-scaled semiconductor devices. In order to simulate the charge transport in such ultra-scaled devices with complex architectures and design, we have developed numerous simulation modules based on various simulation approaches. Currently, NESS contains a drift-diffusion, Kubo-Greenwood, and non-equilibrium Green's function (NEGF) modules. All modules are numerical solvers which are implemented in the C++ programming language, and all of them are linked and solved self-consistently with the Poisson equation. Here, we have deployed some of those modules to showcase the capabilities of NESS to simulate advanced nano-scale semiconductor devices. The devices simulated in this paper are chosen to represent the current state-of-the-art and future technologies where quantum mechanical effects play an important role. Our examples include ultra-scaled nanowire transistors, tunnel transistors, resonant tunneling diodes, and negative capacitance transistors. Our results show that NESS is a robust, fast, and reliable simulation platform which can accurately predict and describe the underlying physics in novel ultra-scaled electronic devices.