Glyphosate Adsorption from Water Using Hierarchically Porous Metal–Organic Frameworks

The selective removal of one ligand in mixed-ligand MOFs upon thermolysis provides a powerful strategy to introduce additional mesopores without affecting the overall MOF structure. By varying the initial ligand ratio, MOFs of the MIL-125-Ti family with two distinct hierarchical pore architectures are synthesized, resembling either large cavities or branching fractures. The performance of the resulting hierarchically porous MOFs is evaluated toward the adsorptive removal of glyphosate (N-(phosphonomethyl)glycine) from water, and the adsorption kinetics and mechanism are examined. Due to their strong affinity for phosphoric groups, the numerous Ti–OH groups resulting from the selective ligand removal act as natural anchor points for effective glyphosate uptake. The relationships between contact duration, glyphosate concentration, and adsorbent dosage are investigated, and the impact of these parameters on the effectiveness of glyphosate removal from contaminated water samples is examined. The introduction of additional mesopores has increased the adsorption capacities by nearly 3 times with record values exceeding 440.9 mg g⁻¹, which ranks these MOFs among the best-reported adsorbents.     

Charge Transport Calculation along Two-Dimensional Metal/Semiconductor/Metal Systems

Two-dimensional transistors are promising candidates for the next generation of nanoscale devices. Like the other alternatives, they also encounter problems such as instability under standard condition (STP), low channel mobility, small band gaps, and difficulty to integrate metal contacts. The latter poses a great challenge since metal/semiconductor interface significantly affects the transistor‘s performance. Some of these obstacles can be solved by using two-dimensional transition metal di-chalcogenides (TMDC) materials. In this study, we performed charge transport calculation based on density functional theory (DFT) followed by wave dynamics to evaluate the performance of six two-dimensional TMDC metal/semiconductor/metal systems. Each semiconductor monolayer was laterally connected, at both ends to metal contacts consisting of VS₂ or FeS₂ monolayers. We found that charge transport was more efficient in systems containing a CrS₂ semiconductor monolayer compared to systems with MoS₂ or WS₂ as the semiconductor monolayer. The electronic characterization of the monolayer TMDC materials by DFT estimates well the trend in charge transport efficiency calculated using wave packet dynamics.     

Genetic homogeneity of autoimmune polyglandular disease type I

Autoimmune polyglandular disease type I (APECED) is an autosomal recessive autoimmune disease (MIM 240300) characterized by hypoparathyroidism, primary adrenocortical failure, and chronic mucocutaneous candidiasis. The disease is highly prevalent in two isolated populations, the Finnish population and the Iranian Jewish one. Sporadic cases have been identified in many other countries, including almost all European countries. The APECED locus has previously been assigned to chromosome 21q22.3 by linkage analyses in 14 Finnish families. Locus heterogeneity is a highly relevant question in this disease affecting multiple tissues and with great phenotypic diversity. To solve this matter, we performed linkage and haplotype analyses on APECED families rising from different populations. Six microsatellite markers on the critical chromosomal region of 2.6 cM on 21q22.3 were analyzed. Pairwise linkage analyses revealed significant LOD scores for all these markers, maximum LOD score being 10.23. The obtained haplotype data and the geographic distribution of the great-grandparents of the Finnish APECED patients suggest the presence of one major, relatively old mutation responsible for approximately 90% of the Finnish cases. Similar evidence for one founder mutation was also found in analyses of Iranian Jewish APECED haplotypes. These haplotypes, however, differed totally from the Finnish ones. The linkage analyses in 21 non-Finnish APECED families originating from several European countries provided independent evidence for linkage to the same chromosomal region on 21q22.3 and revealed no evidence for locus heterogeneity. The haplotype analyses of APECED chromosomes suggest that in different populations APECED is due to a spectrum of mutations in a still unknown gene on chromosome 21.     

Design considerations for a general-purpose microprocessor

The authors examine the performance, cost, and schedule tradeoffs made for the NS 32532, a 32-bit general-purpose microprocessor. Among its features are a 30-MHz clock frequency, three on-chip caches, a four-stage pipeline, and dedicated mechanisms for multiprocessing support. The authors describe the design constraints set by the VLSI processing and packaging technologies. They address the issue of market requirements by examining the software and hardware considerations for the microprocessor's target applications. After describing the functional partitioning choices, including the means for supporting a memory hierarchy and floating-point operations, they present the NS32532's microarchitecture. They then examine the microprocessor's system interface, the memory reference transactions, and the instruction-flow and data-flow monitoring mechanisms. Finally, the authors present an overview of the methodology adopted to accomplish the design within a strict schedule while achieving full functionality and meeting cost and performance goals     

Modeling Diffusion in Functional Materials: From Density Functional Theory to Artificial Intelligence

Diffusion describes the stochastic motion of particles and is often a key factor in determining the functionality of materials. Modeling diffusion of atoms can be very challenging for heterogeneous systems with high energy barriers. In this report, popular computational methodologies are covered to study diffusion mechanisms that are widely used in the community and both their strengths and weaknesses are presented. In static approaches, such as electronic structure theory, diffusion mechanisms are usually analyzed within the nudged elastic band (NEB) framework on the ground electronic surface usually obtained from a density functional theory (DFT) calculation. Another common approach to study diffusion mechanisms is based on molecular dynamics (MD) where the equations of motion are solved for every time step for all the atoms in the system. Unfortunately, both the static and dynamic approaches have inherent limitations that restrict the classes of diffusive systems that can be efficiently treated. Such limitations could be remedied by exploiting recent advances in artificial intelligence and machine learning techniques. Here, the most promising approaches in this emerging field for modeling diffusion are reported. It is believed that these knowledge‐intensive methods have a bright future ahead for the study of diffusion mechanisms in advanced functional materials.     

Strong Band Gap Blueshift in Copper (I) Oxide Semiconductor via Bioinspired Route

Semiconductors have numerous applications in both science and technology. Several methods have been developed to engineer their band gap, which is one of the most important parameters of semiconductors. Here, it is shown that the incorporation of various amino acids into the crystal lattice of copper (I) oxide, akin to the way living organisms incorporate organic macromolecules into minerals during biomineralization, leads to significant shrinkage in the volume of the host unit cell and a strong blueshift in the band gap of up to ≈18%. In examining the potential location of the bio‐organic molecules within the inorganic host's lattice, a very good fit between the proposed model of incorporation and experimental findings is found. The bioinspired phenomenon of band gap widening is thought to be attributable to the void‐induced quantum confinement effect, even though observed in micrometer‐sized crystals. This hypothesis is supported by developing a tight‐binding model that is found to fit well with the experimental data. The outcome of this research could profoundly impact the fields of light‐emitting and spin‐based devices as well as opens up a new bioinspired route to tune the band gap of semiconductors.     

Collaborative information acquisition for data-driven decisions

Data-driven predictive models are routinely used by government agencies and industry to improve the efficiency of their decision-making. In many cases, agencies acquire training data over time, incurring both direct and opportunity costs. Active learning can be used to acquire particularly informative training data that improve learning cost-effectively. However, when multiple models are used to inform decisions, prior work on active learning has significant limitations: either it improves the accuracy of predictive models without regard to how accuracy affects decision making or it addresses only decisions informed by a single predictive model. We propose that decisions informed by multiple models warrant a new kind of Collaborative Information Acquisition (CIA) policy that allows multiple learners to reason collaboratively about informative acquisitions. This paper focuses on tax audit decisions, which affect a vital revenue source for governments worldwide. Because audits are costly to conduct, active learning policies can help identify particularly informative audits to improve future decisions. However, existing active learning models are poorly suited to audit decisions, because audits are best informed by multiple predictive models. We develop a CIA policy to improve the decisions the models inform, and we demonstrate that CIA can substantially increase sales tax revenues. We also demonstrate that the CIA policy can improve decisions to target directly individuals in a donation campaign. Finally, we discuss and demonstrate the risks for decision making of the naive use of existing active learning policies.     

Progressive nemaline rod myopathy in a woman coinfected with HIV-1 and HTLV-2

A putative ubiquitin protein ligase (E3-CaM) which cooperates with UBC4 in selectively ubiquitinating calmodulin has been partially purified from Saccharomyces cerevisiae. Ca2+ was required for this activity and monoubiquitinated calmodulin was the main product of the reaction. The apparent Km of E3-CaM for calmodulin was approximately 1 microM which is of the same order of magnitude as the concentration of calmodulin in yeast cells. Proteins which are good substrates for other E3s (E3 alpha or E3-R) were not ubiquitinated by E3-CaM. Lower but significant activities of E3-CaM were observed when UBC1 replaced UBC4.     

Physical properties of hydrocolloid wet glues

The potential properties of 26 gums to serve as a basis for wet-gum glues were studied. Preliminary tests revealed that only 13 of these, namely gum talha, gum ghatti, gum karaya, gum tragacanth, arabinogalactan, dextran, pectin, tapioca-dextrin, carboxymethyl cellulose (CMC), methyl cellulose (MC), hydroxypropyl cellulose (HPC), hydroxypropylmethyl cellulose (HPMC) and carbopol, can serve as bioadhesives in hydrophilic systems. Wet glues were produced from these hydrocolloids. They were tested over a wide range of loadings, i.e. 10–75% (wlw). The color and pH of each glue were determined. Their ability to adhere to two separate films—cellulose acetate and a skin-surface model—was studied. After checking the performance of the glues by peel testing, seven gums were chosen for further study. Adhesion was evaluated by tensile-bond and lap-shear tests. The deformation rate, the adhesive layer thickness, the degree of hydration of the films and glue, the length of drying time, and the type of hydrocolloid used were found to influence the wet glue bond strength.