There is a growing awareness of the importance of higher education in Sweden to reduce social differences in society. There are also various mechanisms that individuals relate to that favour either the status quo or change based on an ideal of higher education. Individuals live in a geographical context with a number of ‘key actors’ who influence the perception of higher education with varying degrees of intensity. Paradoxically, despite several reforms to broaden recruitment, it can be seen that relative inequalities persist in terms of residents with higher education in Sweden, not least from a regional perspective. The purpose of this article is to shed light on geographical differences in the higher education level of the population over time from a Swedish perspective. The study shows that higher education has a geographical centre-periphery perspective, but not exclusively. There are thus additional influencing factors that in various ways relate to the social context in which the individual is located. We can conclude from our empirical data that the reforms implemented to broaden recruitment have not had the desired effect, especially for the group of men. We find it likely that what differentiates women and men is who their individual ‘key players’ are and how they interact. From an academic education perspective and as an intermediary of higher education, there is therefore a challenge to be able to identify who these “key players” are in order to be able to be an important actor in contributing to the desired broader recruitment that the government is striving to achieve.
Uroporphyrin (UP) is a porphyrin compound with medical applications and a key precursor for heme biosynthesis. However, there is no biosynthetic strategy for UP production. In this study, we present a novel bioprocess for enhanced production of UP in engineered Escherichia coli. We first implemented the Shemin/C4 pathway heterologously in an E. coli strain with an enlarged intracellular pool of succinyl-CoA. Using a plasmid with the trc promoter regulating the expression of a synthesized gene operon, the effects of key pathway genes, including hemA, hemB, hemC, and hemD, on UP biosynthesis were characterized. By cultivating the resulting engineered E. coli strains in a batch bioreactor with 30 g/L glycerol under aerobic conditions, up to 901.9 mg/L UP was produced. Most of the synthesized UP was extracellularly secreted with a high purity more than 80 wt%, facilitating its downstream purification. The study paves the way for large-scale bio-based production of UP using synthetic biology and metabolic engineering strategies.
Thioredoxin-interacting protein (TXNIP) plays a critical role in regulation of cellular redox reactions and inflammatory responses by interacting with thioredoxin (TRX) or the inflammasome. The role of TXNIP in lung fibrosis and molecular regulation of its stability have not been well studied. Therefore, here we investigated the molecular regulation of TXNIP stability and its role in TGF-β1-mediated signaling in lung fibroblasts. TXNIP protein levels were significantly decreased in lung tissues from bleomycin-challenged mice. Overexpression of TXNIP attenuated transforming growth factor-β1 (TGF-β1)-induced phosphorylation of Smad2/3 and fibronectin expression in lung fibroblasts, suggesting that decrease in TXNIP may contribute to the pathogenesis of lung fibrosis. Further, we observed that TGF-β1 lowered TXNIP protein levels, while TXNIP mRNA levels were unaltered by TGF-β1 exposure. TGF-β1 induced TXNIP degradation via the ubiquitin-proteasome system. A serine residue mutant (TNXIP-S308A) was resistant to TGF-β1-induced degradation. Furthermore, downregulation of ubiquitin-specific protease-13 (USP13) promoted the TGF-β1-induced TXNIP ubiquitination and degradation. Mechanistic studies revealed that USP13 targeted and deubiquitinated TXNIP. The results of this study revealed that the decrease of TXNIP in lungs apparently contributes to the pathogenesis of pulmonary fibrosis and that USP13 can target TXNP for deubiquitination and regulate its stability.
The wheel hub is an important part of the automobile, and machining affects its service life and driving safety. With the increasing demand for wheel productivity and machining accuracy in the automotive transport sector, automotive wheel production lines are gradually replacing human production. However, the technical difficulties of conventional automotive wheel production lines include insufficient intelligence, low machining precision, and large use of cutting fluid. This paper aims to address these research constraints. The intelligent, sustainable manufacturing production line for automobile wheel hub is designed. First, the machining of automotive wheel hubs is analyzed, and the overall layout of the production line is designed. Next, the process equipment system including the fixture and the minimum quantity lubrication (MQL) system are designed. The fixture achieves self-positioning and clamping functions through a linkage mechanism and a crank–slider mechanism, respectively, and the reliability of the mechanism is analyzed. Finally, the trajectory planning of the robot with dual clamping stations is performed by RobotStodio. Results show the machining parameters for a machining a wheel hub with a diameter of 580 mm are rotational speed of 2500 rpm, cutting depth of 4 mm, feed rate of 0.5 mm/r, and minimum clamping force of 10881.75 N. The average time to move the wheel hub between the roller table and each machine tool is 27 s, a reduction of 6 s compared with the manual handling time. The MQL system effectively reduces the use of cutting fluid. This production line can provide a basis and reference for actual production by reasonably planning the wheel hub production line.
This paper focuses a novel non-isolated coupled inductor based DC-DC converter with excessive VG (voltage gain) is analyzed with a state-space modeling technique. It builds up of using three diodes, three capacitors, an inductor and CI (coupled inductor). The main switch S is turn on due to body diode and voltage stress is reduced at the switch S by using diode D1 and Capacitor C1. This paper focuses on design modelling, mathematical calculations and operation principle of DC-DC converter is discussed with state-space modelling technique. The performance has been presented for two different voltages for EV applications, i.e., 12 V, 48 V as input voltages with a high step-up outputs of 66 V and 831.7 V respectively. The converter stability is studied and determined the bode plot along with simulation performance results which are carried out using MATLAB R2022B.
In today’s world, when there is a constant fight against organized crime and terrorism, when we have cases of mass accidents (plane crashes, train crashes, buses, etc.), the constant need for precise and quick identification of persons is evident in these cases. When we have situations with a large number of dead in various conditions, as well as complete or only parts of the body being on the spot, there is a need to use scientific and forensic methods in order to find out the reliable identity of these people. Furthermore, there is a need, in some cases, to identify persons who committed suicide, were killed, or died a natural death (accidental death) and who do not have documents according to which their identity can be determined. The aim of this paper will, however, be to identify a group of persons who need to be identified, known as unidentified corpses. Method. Describe and discuss the way of determining identity based on dactyloscopic data, which provides accurate and unambiguous identification, using fingerprints. Results. The identity was determined in 1271 cases of unidentified corpses by dactyloscopic comparison of fingerprints with a database containing fingerprints of about 8,000,000 indisputably identified persons. It was confirmed in 1139 cases. Conclusion. The high degree of identification in our research, as much as 89.6%, makes this method rightly represented as a standard method for confirming a person’s identity.
This article presents the opportunities for constructing a global data base picturing underlying trends that drive global climate change. Energy-related CO2 emissions currently represent the key impact on climate change and thus become here the object of deep, long-term and historiographic analysis. In order to embrace all involved domains of technology, energy economy, fuel shares, economic efficacity, economic structure and population, a “Global Change Data Base” (GCDB) is suggested, based on earlier worldwide accepted data repositories. Such a GCDB works through regressions and statistical analysis of time series of data (on extensive magnitudes such as energy demand, population or Gross Domestic Product, GDP) as well as generation of derived data such as quotients of the former, yielding intensive magnitudes that describe systems and their structural properties. Moreover, the GCDB sets out to compute the first and second time derivatives of said magnitudes (and their percentual shares) which indicate new long-term developments already at very early phases. The invitation to participate in this foresight endeavour is extended to all readers. First preliminary GCDB results quantitatively portray the evolutionary structural global dynamics of economic growth, sectoral economic shifts, the shifts within energy carriers in various economic sectors, the ongoing improvements of energy intensity and energy efficiency in many economic sectors, and the structural changes within agricultural production and consumption systems.
In this paper, an autonomous system is developed for drone racing. On account of their vast consumption of computing resources, the methods for visual navigation commonly employed are discarded, such as visual-inertial odometry (VIO) or simultaneous localization and mapping (SLAM). A series of navigation algorithms for autonomous drone racing, which can operate without the aid of the information on the external position, are proposed: one for lightweight gate detection, achieving gates detection with a frequency of 60 Hz; one for direct collision detection, seeking the maximum passability in-depth images. Besides, a velocity planner is adopted to generate velocity commands according to the results from visual navigation, which are enabled to perform a guidance role when the drone is approaching and passing through gates, assisting it in avoiding obstacles and searching for temporarily invisible gates. The approach proposed above has been demonstrated to successfully help our drone passing-through complex environments with a maximum speed of 2.5 m/s and ranked first at the 2022 RoboMaster Intelligent UAV Championship.
Photofermentative hydrogen production with non-sulfur purple bacteria like Cereibacter sphaeroides (formerly Rhodobacter sphaeroides) is a promising and sustainable process to convert organic waste into the energy carrier hydrogen gas. However, this conversion is inhibited by elevated organic nitrogen concentrations in the substrate, which limits its applicability to nitrogen-poor organic waste. We present genomic and transcriptomic insights into a substrain of Cereibacter sphaeroides strain 2.4.1 that shows unexpected high levels of photofermentative hydrogen evolution when fed with glutamate. Genome sequencing revealed 222 single nucleotide variances (SNVs) between the reference genome of C. sphaeroides strain 2.4.1 and the analyzed substrain H2. These affect 61 protein coding genes. A leucine-proline exchange is present in the σ54 factor (rpoN2 gene), a global hydrogen and nitrogen metabolism regulator. We propose a model how this mutation alters DNA-binding properties that explain the unexpected organic nitrogen tolerance of hydrogen production. Transcriptomic analyses under varying glutamate concentrations support this finding. Thus, we present the first thorough genomic and transcriptomic analysis of a Cereibacter strain that shows promising metabolic characteristics for biotechnological hydrogen gas production from organic waste. These results suggest a potential target for strain optimization. Possibly, our key finding can be transferred to other hydrogen producing microorganisms.