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  • Investigation of important biochemical compounds from selected freshwater macroalgae and their role in agriculture

    Shah, Zahir; Badshah, Syed Lal; Iqbal, Arshad; Shah, Zamarud; Emwas, Abdul-Hamid M.; Jaremko, Mariusz (Chemical and Biological Technologies in Agriculture, Springer Science and Business Media LLC, 2022-01-15) [Article]
    Background Freshwater macroalgae possess a number of important secondary metabolites. They are an unexplored source of medicinal compounds. In this study, three freshwater macroalgae—$\textit{Chara vulgaris}$, $\textit{Cladophora glomerata}$ and $\textit{Spirogyra crassa}$—were collected from the river Swat and the river Kabul in the Charsadda district of Khyber Pakhtunkhwa, Pakistan. To assess the role of freshwater macroalgae in agriculture, various experiments were performed on their extracts. Methanolic extract of the three macroalgae were first analyzed through gas chromatography–mass spectrometry (GC–MS) for the presence of important medicinal secondary metabolites. The methanol based macroalgae extracts were tested for antibacterial, insecticidal, cytotoxic and phytotoxic activities. Results Initially, the algae were dried, crushed and treated with methanol for the extraction of secondary metabolites. The GC–MS results contained several important long chain fatty acids and other related long-chain hydrocarbons, such as alkanes and alkenes. Several benzene derivatives were also detected during the course of the investigation. Several of these compounds have established roles in the treatment of human ailments and can be supplied to farm animals. For example, phenylephrine is a decongestant, dilates pupils, increases blood pressure and helps in relieving hemorrhoids. Hexahydropseudoionone has uses in perfumes and other cosmetics. Several essential oils were also detected in the methanolic extract of the three macroalgae that can be utilized in various industrial products. Bioassays showed that these algal extracts—especially the $\textit{Spirogyra}$ sp. extract—contain moderate to maximum bioactivity. Conclusions Macroalgae possess important secondary metabolites with medicinal properties. These secondary metabolites can be used as biopesticides, plant growth enhancers, and remedies for various diseases in farm animals and for the control of weeds. They can be further explored for isolation and purification of useful biochemical compounds.
  • Underestimated PAH accumulation potential of blue carbon vegetation: Evidence from sedimentary records of saltmarsh and mangrove in Yueqing Bay, China.

    Huang, Runqiu; Zhang, Chunfang; Xu, Xiangrong; Jin, Runjie; Li, Dan; Christakos, George; Xiao, Xi; He, Junyu; Agusti, Susana; Duarte, Carlos M.; Wu, Jiaping (The Science of the total environment, Elsevier BV, 2022-01-13) [Article]
    Sediments of blue carbon vegetation are becoming a sink of natural and anthropogenic pollutants, such as polycyclic aromatic hydrocarbons (PAHs). However, the extent to which PAHs are accumulated and varied in blue carbon sediments, and the impact of blue carbon vegetation on the accumulation and retention capacity of PAHs, have been poorly explored. This study examines the sedimentary records of PAHs in profiles from mangrove plantations, saltmarsh, and mudflat in Ximen Island and Maoyan Island of Yueqing Bay, China. The existence of blue carbon vegetation provides a sheltered environment for the accelerated burial of sediment and OC. Decadal PAH sedimentation records show staged changes characterized by the emission of PAHs and colonization of blue carbon vegetation, reflecting the accelerated burial of PAHs in sediments by blue carbon vegetation colonization. In addition, the colonization of blue carbon vegetation contributes to the shift of PAH compositions in sediments. This study provides new insights into the underestimated PAH accumulation potential and retention capacity of blue carbon vegetation and the corresponding underlying sediments, supporting the environmental benefits of blue carbon vegetation.
  • Study of the Effect of Research Octane Number on the Auto-Ignition of Lubricant Oil Surrogates (n-Hexadecane)

    Maharjan, Sumit; Elbaz, Ayman M.; Roberts, William L. (ACS Omega, American Chemical Society (ACS), 2022-01-12) [Article]
    Engine oil is considered one of the sources for pre-ignition in downsized boosted direct injection spark-ignited engines. When interacting with fuel sprayed in the combustion chamber, engine oil forms an ignitable mixture and can cause an ignition event before firing the spark plug. Because high research octane number (RON) fuels are difficult to auto-ignite and tend to suppress the knock in an internal combustion engine, studying their interaction with engine oil is essential. Hence, in the current study, a suitable lubricant oil surrogate, namely, n-hexadecane, is mixed with iso-octane and n-heptane at different concentrations to investigate the auto-ignition behavior at elevated pressures. Five sets of fuels (PRF0, PRF20, PRF50, PRF80, and PRF100) were prepared to get a wide range of RONs and blended with n-hexadecane at 15, 25, 35, and 45% mixture concentrations (vol %). These experiments were conducted in a constant volume combustion chamber, keeping the initial temperature constant at 300 °C. A single droplet of the mixture was suspended on a thermocouple bead to record the droplet’s lifetime temperature. It was observed that hexadecane mixed with PRF0, PRF20, PRF50, and PRF80 showed similar auto-ignition behaviors. The time of ignition (TI) for these mixtures initially increased until 25% concentration of the fuel in n-hexadecane, and further addition of fuels to 35% and higher concentrations showed a gradual decrease in TI. Ignition of mixtures with 35% and 45% fuel concentrations is attributed to n-heptane, as its low temperature chemistry is the dominant factor in its high reactivity compared to iso-octane. TI increased with the increasing concentration of PRF100 mixtures in hexadecane, unlike other PRF fuels tested in this study. This is because iso-octane is a high RON fuel with a higher auto-ignition temperature, making it challenging to auto-ignite.
  • Rice domestication.

    Fornasiero, Alice; Wing, Rod Anthony; Ronald, Pamela (Current biology : CB, Elsevier BV, 2022-01-11) [Article]
    Rice is a staple food crop for more than one-third of the global population (, of which 90% live at or near the poverty line. Thus, rice genetic improvement is important for global food security and is critical for enhancing socioeconomic benefits and reducing the environmental impacts of agriculture. In continued efforts to address the long-standing problem of food security and sustainable agriculture, scientists are utilizing genes from diverse varieties of rice to improve the resilience of rice to pests, diseases and environmental stress. This Primer describes the history of rice domestication, the importance of wild relatives of rice for crop improvement, and the domestication of wild species of rice not previously planted by farmers - a new approach called neodomestication.
  • Air-Processable and Thermally Stable Hole Transport Layer for Non-Fullerene Organic Solar Cells

    Bertrandie, Jules; Sharma, Anirudh; Gasparini, Nicola; Rosas Villalva, Diego; Paleti, Sri Harish Kumar; Wehbe, Nimer; Troughton, Joel; Baran, Derya (ACS Applied Energy Materials, American Chemical Society (ACS), 2022-01-10) [Article]
    Power conversion efficiencies (PCEs) of organic solar cells (OSCs) have now surpassed 19%. This has led to an increased focus on developing devices using methods and materials that are scalable, processable under ambient air atmospheres, and stable. However, current materials fall short of the essential requirements for stability and processability needed for cost-effective large-scale fabrication of high-performing OSCs. Here, we report a hybrid solution-processable hole transport layer (HTL) based on tantalum-doped tungsten oxide (TaWOx) nanoparticles and poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) demonstrating good wettability over the hydrophobic active layer. N-i-p-type OSCs that are processed fully under ambient conditions, based on a polymer donor and a non-fullerene acceptor incorporating a combined TaWOx-PEDOT:PSS layer as HTL deliver a power conversion efficiency of 8.6%. OSCs utilizing the TaWOx-PEDOT:PSS HTL demonstrate improved thermal stability compared to devices based on the previously reported solution-processed MoOx-PEDOT:PSS HTL, which was found to severely degrade upon thermal treatment at 85 °C. Photoelectron spectroscopy and secondary ion mass spectrometry (SIMS) reveal that the MoOx-PEDOT:PSS HTL is prone to thermally induced intermixing with the underlying active layer, resulting in unfavorable changes in the interfacial energetics. No significant heat-induced changes are observed in the case of the TaWOx-PEDOT:PSS HTL when annealed up to 120 °C, imparting enhanced thermal stability to the devices. Improved wettability on hydrophobic surfaces, combined with air processability and enhanced thermal stability makes TaWOx-PEDOT:PSS a promising HTL material for fabricating stable NFA solar cells using roll-to-roll compatible printing and coating methods.
  • A Universal Co-Solvent Evaporation Strategy Enables Direct Printing of Perovskite Single Crystals for Optoelectronic Device Applications

    Corzo Diaz, Daniel Alejandro; Wang, Tonghui; Gedda, Murali; Yengel, Emre; Khan, Jafar Iqbal; Li, Ruipeng; Niazi, Muhammad Rizwan; Huang, Zhengjie; Kim, Taesoo; Baran, Derya; Sun, Dali; Laquai, Frédéric; Anthopoulos, Thomas D.; Amassian, Aram (Advanced Materials, Wiley, 2022-01-10) [Article]
    Solution-processed metal halide perovskite single crystals (SCs) are in high demand for a growing number of emerging device applications due to their superior optoelectronic properties compared to polycrystalline thin films. However, the historical focus on thin film optoelectronic and photovoltaic devices explains the absence of methods suitable for facile, scalable and high throughput fabrication of precision-engineered and positioned SCs and arrays. Here, we present a universal co-solvent evaporation (CSE) strategy by which perovskite SCsand arrays are produced directly on substrates from individual drying droplets in a single step within minutes at room temperature. The CSE strategy successfully guides supersaturation of drying droplets to suppress all unwanted crystallization pathways and is shown to produce SCsof a wide variety of three-dimensional (3D), quasi-two dimensional (2D), and mixed cation/halideperovskites. The drying droplet approach works with commonly used solvents, making it universal. Importantly, the CSE strategy ensures the SC consumes the precursor in its entirety, leaving little to no residue on substrates, which is crucial for enabling fabrication of SC arrays on large areas via printing and coating techniques. We go on to demonstrate direct on-chip fabrication of 3D and quasi-2D perovskite photodetector devices with outstanding performance. Our approach shows that metal halide perovskite SCs can now be produced on substrates from a drying solution via a wide range of solution processing methods, including microprinting and scalable, high throughput coating methods.
  • In Vitro and In Silico Approaches for the Evaluation of Antimicrobial Activity, Time-Kill Kinetics, and Anti-Biofilm Potential of Thymoquinone (2-Methyl-5-propan-2-ylcyclohexa-2,5-diene-1,4-dione) against Selected Human Pathogens

    Qureshi, Kamal A.; Imtiaz, Mahrukh; Parvez, Adil; Rai, Pankaj K.; Jaremko, Mariusz; Emwas, Abdul-Hamid M.; Bholay, Avinash D.; Fatmi, Muhammad Qaiser (Antibiotics, MDPI AG, 2022-01-10) [Article]
    Thymoquinone (2-methyl-5-propan-2-ylcyclohexa-2,5-diene-1,4-dione; TQ), a principal bioactive phytoconstituent of Nigella sativa essential oil, has been reported to have high antimicrobial potential. Thus, the current study evaluated TQ’s antimicrobial potential against a range of selected human pathogens using in vitro assays, including time-kill kinetics and anti-biofilm activity. In silico molecular docking of TQ against several antimicrobial target proteins and a detailed intermolecular interaction analysis was performed, including binding energies and docking feasibility. Of the tested bacteria and fungi, S. epidermidis ATCC 12228 and Candida albicans ATCC 10231 were the most susceptible to TQ, with 50.3 ± 0.3 mm and 21.1 ± 0.1 mm zones of inhibition, respectively. Minimum inhibitory concentration (MIC) values of TQ are in the range of 12.5–50 µg/mL, while minimum biocidal concentration (MBC) values are in the range of 25–100 µg/mL against the tested organisms. Time-kill kinetics of TQ revealed that the killing time for the tested bacteria is in the range of 1–6 h with the MBC of TQ. Anti-biofilm activity results demonstrate that the minimum biofilm inhibitory concentration (MBIC) values of TQ are in the range of 25–50 µg/mL, while the minimum biofilm eradication concentration (MBEC) values are in the range of 25–100 µg/mL, for the tested bacteria. In silico molecular docking studies revealed four preferred antibacterial and antifungal target proteins for TQ: D-alanyl-D-alanine synthetase (Ddl) from Thermus thermophilus, transcriptional regulator qacR from Staphylococcus aureus, N-myristoyltransferase from Candida albicans, and NADPH-dependent D-xylose reductase from Candida tenuis. In contrast, the nitroreductase family protein from Bacillus cereus and spore coat polysaccharide biosynthesis protein from Bacillus subtilis and UDP-N-acetylglucosamine pyrophosphorylase from Aspergillus fumigatus are the least preferred antibacterial and antifungal target proteins for TQ, respectively. Molecular dynamics (MD) simulations revealed that TQ could bind to all four target proteins, with Ddl and NADPH-dependent D-xylose reductase being the most efficient. Our findings corroborate TQ’s high antimicrobial potential, suggesting it may be a promising drug candidate for multi-drug resistant (MDR) pathogens, notably Gram-positive bacteria and Candida albicans.
  • Digital E. coli Counter: A Microfluidics and Computer Vision-Based DNAzyme Method for the Isolation and Specific Detection of E. coli from Water Samples

    Rauf, Sakandar; Tashkandi, Nouran Abdulatif; De Oliveira Filho, José Ilton; Oviedo-Osornio, Claudia Iluhí; Danish, Muhammad S.; Hong, Pei-Ying; Salama, Khaled N. (Biosensors, MDPI AG, 2022-01-10) [Article]
    Biological water contamination detection-based assays are essential to test water quality; however, these assays are prone to false-positive results and inaccuracies, are time-consuming, and use complicated procedures to test large water samples. Herein, we show a simple detection and counting method for E. coli in the water samples involving a combination of DNAzyme sensor, microfluidics, and computer vision strategies. We first isolated E. coli into individual droplets containing a DNAzyme mixture using droplet microfluidics. Upon bacterial cell lysis by heating, the DNAzyme mixture reacted with a particular substrate present in the crude intracellular material (CIM) of E. coli. This event triggers the dissociation of the fluorophore-quencher pair present in the DNAzyme mixture leading to a fluorescence signal, indicating the presence of E. coli in the droplets. We developed an algorithm using computer vision to analyze the fluorescent droplets containing E. coli in the presence of non-fluorescent droplets. The algorithm can detect and count fluorescent droplets representing the number of E. coli present in the sample. Finally, we show that the developed method is highly specific to detect and count E. coli in the presence of other bacteria present in the water sample.
  • Efficiently Disentangle Causal Representations

    Li, Yuanpeng; Hestness, Joel; Elhoseiny, Mohamed; Zhao, Liang; Church, Kenneth (arXiv, 2022-01-06) [Preprint]
    This paper proposes an efficient approach to learning disentangled representations with causal mechanisms based on the difference of conditional probabilities in original and new distributions. We approximate the difference with models' generalization abilities so that it fits in the standard machine learning framework and can be efficiently computed. In contrast to the state-of-the-art approach, which relies on the learner's adaptation speed to new distribution, the proposed approach only requires evaluating the model's generalization ability. We provide a theoretical explanation for the advantage of the proposed method, and our experiments show that the proposed technique is 1.9--11.0$\times$ more sample efficient and 9.4--32.4 times quicker than the previous method on various tasks. The source code is available at \url{}.
  • Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat

    Silva, Paula; Evers, Byron; Kieffaber, Alexandria; Wang, Xu; Brown, Richard; Gao, Liangliang; Fritz, Allan K.; Crain, Jared; Poland, Jesse (Cold Spring Harbor Laboratory, 2022-01-06) [Preprint]
    Barley yellow dwarf (BYD) is one of the major viral diseases of cereals. Phenotyping BYD in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to, i) evaluate the use of high-throughput phenotyping (HTP) from unmanned aerial systems to improve BYD assessment and selection, ii) identify genomic regions associated with BYD resistance, and iii) evaluate genomic prediction models ability to predict BYD resistance. Up to 107 wheat lines were phenotyped during each of five field seasons under both insecticide treated and untreated plots. Across all seasons, BYD severity was lower with the insecticide treatment and plant height (PTHTM) and grain yield (GY) showed increased values relative to untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying resistance gene $\textit{Bdv2}$ on chromosome 7DL. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for resistance on chromosome 5AS. Given the variable heritability of the trait (0.211 0.806), we obtained relatively good predictive ability for BYD severity ranging between 0.06 0.26. Including $\textit{Bdv2}$ on the predictive model had a large effect for predicting BYD but almost no effect for PTHTM and GY. This study was the first attempt to characterize BYD using field-HTP and apply GS to predict the disease severity. These methods have the potential to improve BYD characterization and identifying new sources of resistance will be crucial for delivering BYD resistant germplasm.
  • Scalable CMOS-BEOL compatible AlScN/2D Channel FE-FETs

    Kim, Kwan-Ho; Oh, Seyong; Fiagbenu, Merrilyn Mercy Adzo; Zheng, Jeffrey; Musavigharavi, Pariasadat; Kumar, Pawan; Trainor, Nicholas; Aljarb, Areej; Wan, Yi; Kim, Hyong Min; Katti, Keshava; Tang, Zichen; Tung, Vincent; Redwing, Joan; Stach, Eric A.; III, Roy H. Olsson; Jariwala, Deep (arXiv, 2022-01-06) [Preprint]
    Intimate integration of memory devices with logic transistors is a frontier challenge in computer hardware. This integration is essential for augmenting computational power concurrently with enhanced energy efficiency in big-data applications such as artificial intelligence. Despite decades of efforts, reliable, compact, energy efficient and scalable memory devices are elusive. Ferroelectric Field Effect Transistors (FE-FETs) are a promising candidate but their scalability and performance in a back-end-of-line (BEOL) process remain unattained. Here, we present scalable BEOL compatible FE-FETs using two-dimensional (2D) MoS2 channel and AlScN ferroelectric dielectric. We have fabricated a large array of FE-FETs with memory windows larger than 7.8 V, ON/OFF ratios of greater than 10^7, and ON current density greater than 250 uA/um, all at ~80 nm channel lengths. Our devices show stable retention up to 20000 secs and endurance up to 20000 cycles in addition to 4-bit pulse programmable memory features thereby opening a path towards scalable 3D hetero-integration of 2D semiconductor memory with Si CMOS logic.
  • Decision trees for regular factorial languages

    Moshkov, Mikhail (arXiv, 2022-01-06) [Preprint]
    In this paper, we study arbitrary regular factorial languages over a finite alphabet $\Sigma$. For the set of words $L(n)$ of the length $n$ belonging to a regular factorial language $L$, we investigate the depth of decision trees solving the recognition and the membership problems deterministically and nondeterministically. In the case of recognition problem, for a given word from $L(n)$, we should recognize it using queries each of which, for some $ i\in \{1,\ldots ,n\}$, returns the $i$th letter of the word. In the case of membership problem, for a given word over the alphabet $\Sigma$ of the length $n$, we should recognize if it belongs to the set $L(n)$ using the same queries. For a given problem and type of trees, instead of the minimum depth $h(n)$ of a decision tree of the considered type solving the problem for $L(n)$, we study the smoothed minimum depth $H(n)=\max\{h(m):m\le n\}$. With the growth of $n$, the smoothed minimum depth of decision trees solving the problem of recognition deterministically is either bounded from above by a constant, or grows as a logarithm, or linearly. For other cases (decision trees solving the problem of recognition nondeterministically, and decision trees solving the membership problem deterministically and nondeterministically), with the growth of $n$, the smoothed minimum depth of decision trees is either bounded from above by a constant or grows linearly. As corollaries of the obtained results, we study joint behavior of smoothed minimum depths of decision trees for the considered four cases and describe five complexity classes of regular factorial languages. We also investigate the class of regular factorial languages over the alphabet $\{0,1\}$ each of which is given by one forbidden word.
  • Decision trees for binary subword-closed languages

    Moshkov, Mikhail (arXiv, 2022-01-05) [Preprint]
    In this paper, we study arbitrary subword-closed languages over the alphabet $\{0,1\}$ (binary subword-closed languages). For the set of words $L(n)$ of the length $n$ belonging to a binary subword-closed language $L$, we investigate the depth of decision trees solving the recognition and the membership problems deterministically and nondeterministically. In the case of recognition problem, for a given word from $L(n)$, we should recognize it using queries each of which, for some $i\in \{1,\ldots ,n\}$, returns the $i$th letter of the word. In the case of membership problem, for a given word over the alphabet $\{0,1\}$ of the length $n$, we should recognize if it belongs to the set $L(n)$ using the same queries. With the growth of $n$, the minimum depth of decision trees solving the problem of recognition deterministically is either bounded from above by a constant, or grows as a logarithm, or linearly. For other types of trees and problems (decision trees solving the problem of recognition nondeterministically, and decision trees solving the membership problem deterministically and nondeterministically), with the growth of $n$, the minimum depth of decision trees is either bounded from above by a constant or grows linearly. We study joint behavior of minimum depths of the considered four types of decision trees and describe five complexity classes of binary subword-closed languages.
  • Operando Monitoring and Deciphering the Structural Evolution in Oxygen Evolution Electrocatalysis

    Zuo, Shouwei; Wu, Zhi-Peng; Zhang, Huabin; Lou, Xiong Wen (David) (Advanced Energy Materials, Wiley, 2022-01-05) [Article]
    The oxygen evolution reaction (OER) acts as the bottleneck of some crucial energy conversion and storage technologies involving water electrolysis, CO2 electrolysis, and metal-air batteries, among others. The challenging sluggish reaction kinetics of the OER can be overcome via developing highly efficient electrocatalysts, which experience a dynamic structural evolution process during the reaction. However, the reaction mechanism of the structural transformation of electrocatalysts during the OER and the structure-activity correlation in understanding the real active sites remain elusive. Fortunately, operando characterizations offer a platform to study the structural evolution processes and the reaction mechanisms of OER electrocatalysts. In this review, using several in situ/operando techniques some recent advances are elaborated with emphases on tracking the structural evolution processes of electrocatalysts, recording the reaction intermediates during electrocatalysis, and building a link between the structure and activity/stability of electrocatalysts. Moreover, theoretical considerations are also discussed to assist operando characterization understanding. Finally, some perspectives are provided which are expected to be helpful to tackle the current challenges in operando monitoring and unraveling the reaction mechanisms of OER electrocatalysts.
  • Thymosin β4 Is an Endogenous Iron Chelator and Molecular Switcher of Ferroptosis

    Lachowicz, Joanna; Pichiri, Gius; Piludu, Marco; Fais, Sara; Orrù, Germano; Congiu, Terenzio; Piras, Monica; Faa, Gavino; Fanni, Daniela; Torre, Gabriele; Lopez, Xabier; Chandra, Kousik; Szczepski, Kacper; Jaremko, Lukasz; Ghosh, Mitra; Emwas , Abdul-Hamid; Castagnola, Massimo; Jaremko, Mariusz; Hannappel, Ewald; Coni, Pierpaolo (International Journal of Molecular Sciences, Research Square Platform LLC, 2022-01-04) [Article]
    Thymosin β4 (Tβ4) was extracted forty years agofrom calf thymus. Since then, it has been identified as a G-actin binding protein involved in blood clotting, tissue regeneration, angiogenesis, and anti-inflammatory processes. Tβ4 has also been implicated in tumor metastasis and neurodegeneration. However, the precise roles and mechanism(s) of action of Tβ4 in these processes remain largely unknown, with the binding of the G-actin protein being insufficient to explain these multi-actions. Here we identify for the first time the important role of Tβ4 mechanism in ferroptosis, an iron-dependent form of cell death, which leads to neurodegeneration and somehow protects cancer cells against cell death. Specifically, we demonstrate four iron2+ and iron3+ binding regions along the peptide and show that the presence of Tβ4 in cell growing medium inhibits erastin and glutamate-induced ferroptosis in the macrophage cell line. Moreover, Tβ4 increases the expression of oxidative stress-related genes, namely BAX, hem oxygenase-1, heat shock protein 70 and thioredoxin reductase 1, which are downregulated during ferroptosis. We state the hypothesis that Tβ4 is an endogenous iron chelator and take part in iron homeostasis in the ferroptosis process. We discuss the literature data of parallel involvement of Tβ4 and ferroptosis in different human pathologies, mainly cancer and neurodegeneration. Our findings confronted with literature data show that controlled Tβ4 release could command on/off switching of ferroptosis and may provide novel therapeutic opportunities in cancer and tissue degeneration pathologies
  • Efficient Importance Sampling Algorithm Applied to the Performance Analysis of Wireless Communication Systems Estimation

    Amar, Eya Ben; Rached, Nadhir Ben; Haji-Ali, Abdul-Lateef; Tempone, Raul (arXiv, 2022-01-04) [Preprint]
    When assessing the performance of wireless communication systems operating over fading channels, one often encounters the problem of computing expectations of some functional of sums of independent random variables (RVs). The outage probability (OP) at the output of Equal Gain Combining (EGC) and Maximum Ratio Combining (MRC) receivers is among the most important performance metrics that falls within this framework. In general, closed form expressions of expectations of functionals applied to sums of RVs are out of reach. A naive Monte Carlo (MC) simulation is of course an alternative approach. However, this method requires a large number of samples for rare event problems (small OP values for instance). Therefore, it is of paramount importance to use variance reduction techniques to develop fast and efficient estimation methods. In this work, we use importance sampling (IS), being known for its efficiency in requiring less computations for achieving the same accuracy requirement. In this line, we propose a state-dependent IS scheme based on a stochastic optimal control (SOC) formulation to calculate rare events quantities that could be written in a form of an expectation of some functional of sums of independent RVs. Our proposed algorithm is generic and can be applicable without any restriction on the univariate distributions of the different fading envelops/gains or on the functional that is applied to the sum. We apply our approach to the Log-Normal distribution to compute the OP at the output of diversity receivers with and without co-channel interference. For each case, we show numerically that the proposed state-dependent IS algorithm compares favorably to most of the well-known estimators dealing with similar problems.
  • Time and space complexity of deterministic and nondeterministic decision trees

    Moshkov, Mikhail (arXiv, 2022-01-04) [Preprint]
    In this paper, we study arbitrary infinite binary information systems each of which consists of an infinite set called universe and an infinite set of two-valued functions (attributes) defined on the universe. We consider the notion of a problem over information system which is described by a finite number of attributes and a mapping corresponding a decision to each tuple of attribute values. As algorithms for problem solving, we use deterministic and nondeterministic decision trees. As time and space complexity, we study the depth and the number of nodes in the decision trees. In the worst case, with the growth of the number of attributes in the problem description, (i) the minimum depth of deterministic decision trees grows either almost as logarithm or linearly, (ii) the minimum depth of nondeterministic decision trees either is bounded from above by a constant or grows linearly, (iii) the minimum number of nodes in deterministic decision trees has either polynomial or exponential growth, and (iv) the minimum number of nodes in nondeterministic decision trees has either polynomial or exponential growth. Based on these results, we divide the set of all infinite binary information systems into five complexity classes, and study for each class issues related to time-space trade-off for decision trees.
  • Heterotrophic Bacterioplankton Growth and Physiological Properties in Red Sea Tropical Shallow Ecosystems With Different Dissolved Organic Matter Sources

    Silva, Luis; Calleja Cortes, Maria de Lluch; Huete-Stauffer, Tamara M.; Ivetic, Snjezana; Ansari, Mohd Ikram; Viegas, Miguel; Moran, Xose Anxelu G. (Frontiers in Microbiology, Frontiers Media SA, 2022-01-03) [Article]
    Despite the key role of heterotrophic bacterioplankton in the biogeochemistry of tropical coastal waters, their dynamics have been poorly investigated in relation to the different dissolved organic matter (DOM) pools usually available. In this study we conducted four seasonal incubations of unfiltered and predator-free seawater (Community and Filtered treatment, respectively) at three Red Sea coastal sites characterized by different dominant DOM sources: Seagrass, Mangrove, and Phytoplankton. Bacterial abundance, growth and physiological status were assessed by flow cytometry and community composition by 16S rRNA gene amplicons. The Seagrass site showed the highest initial abundances (6.93 ± 0.30 × 10$^{5}$ cells mL$^{–1}$), coincident with maximum DOC concentrations (>100 μmol C L$^{–1}$), while growth rates peaked at the Mangrove site (1.11 ± 0.09 d$^{–1}$) and were consistently higher in the Filtered treatment. The ratio between the Filtered and Community maximum bacterial abundance (a proxy for top-down control by protistan grazers) showed minimum values at the Seagrass site (1.05 ± 0.05) and maximum at the Phytoplankton site (1.24 ± 0.30), suggesting protistan grazing was higher in open waters, especially in the first half of the year. Since the Mangrove and Seagrass sites shared a similar bacterial diversity, the unexpected lack of bacterial response to predators removal at the latter site should be explained by differences in DOM characteristics. Nitrogen-rich DOM and fluorescent protein-like components were significantly associated with enhanced specific growth rates along the inshore-offshore gradient. Our study confirms the hypotheses that top–down factors control bacterial standing stocks while specific growth rates are bottom-up controlled in representative Red Sea shallow, oligotrophic ecosystems.
  • CS-Cells: A CRISPR-Cas12 DNA Device to Generate Chromosome-Shredded Cells for Efficient and Safe Molecular Biomanufacturing

    Pantoja Angles, Aarón; Ali, Zahir; Mahfouz, Magdy M. (ACS Synthetic Biology, American Chemical Society (ACS), 2022-01-03) [Article]
    Synthetic biology holds great promise for translating ideas into products to address the grand challenges facing humanity. Molecular biomanufacturing is an emerging technology that facilitates the production of key products of value, including therapeutics and select chemical compounds. Current biomanufacturing technologies require improvements to overcome limiting factors, including efficient production, cost, and safe release; therefore, developing optimum chassis for biomolecular manufacturing is of great interest for enabling diverse synthetic biology applications. Here, we harnessed the power of the CRISPR-Cas12 system to design, build, and test a DNA device for genome shredding, which fragments the native genome to enable the conversion of bacterial cells into nonreplicative, biosynthetically active, and programmable molecular biomanufacturing chassis. As a proof of concept, we demonstrated the efficient production of green fluorescent protein and violacein, an antimicrobial and antitumorigenic compound. Our CRISPR-Cas12-based chromosome-shredder DNA device has built-in biocontainment features providing a roadmap for the conversion of any bacterial cell into a chromosome-shredded chassis amenable to high-efficiency molecular biomanufacturing, thereby enabling exciting and diverse biotechnological applications.
  • Evaluation of Detailed Reaction Models for the Modeling of Double Cellular Structures in Gaseous Nitromethane Detonation

    Chi, Dunstan Y.; Chatelain, Karl P.; Lacoste, Deanna (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]

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