Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of new methionine-based ionic liquid on the CDR1 and CDR2 gene expression on sensitive and resistant strains of Candida albicans

Background and Objectives: Previous researchers showed the antimicrobial ability of ionic liquids (ILs) on different infective agents. ILs can dissolve organic components, especially DNA molecules. Among synthesized eight binary ILs mixtures, we have chosen ([Met-HCl] [PyS]) IL for determining the antifungal ability of IL against Candida albicans cells. Materials and Methods: Well diffusion assay, chrome agar and Germ tube tests were used to detect the Candida samples. PCR, real-time-PCR, and flow cytometry tests were performed to determine the IL's rate of toxic ability. Results: Well diffusion assay revealed the diameters of the growth inhibition zones were the largest in IL with methionine and Proline amino acids. Minimum inhibitory concentration (MIC) and the Minimum fungicidal concentration (MFC) tests showed that they inhibited the growth of the C. albicans at a range from 250 μg/ml for sensitivity and 400 μg/ml for resistance, MIC average of all samples were 341.62 ± 4.153 μg/ml. IL reduced the expression of CDR1 and CDR2 the genes encoded by the major protein of ABC system transporter by 2.1 (P= 0.009) and 1.2 fold (P= 0.693), revealed by PCR and real time-PCR. In the flow cytometry test, there were increasing dead cells after treating with the ([Met-HCl] [PyS]) even in the most resistant strain. Conclusion: The novel IL was effective against the most clinical and standard C. albicans.
A Hybrid Framework for Simulating Actual Evapotranspiration in Data-Deficient Areas: A Case Study of the Inner Mongolia Section of the Yellow River Basin

Evapotranspiration (ET) plays an import role in transferring water and converting energy in the land–atmosphere system. Accurately estimating ET is crucial for understanding global climate change, ecological environmental problems, the water cycle, and hydrological processes. Machine learning (ML) algorithms have been considered as a promising method for estimating ET in recent years. However, due to the limitations associated with the spatial–temporal resolution of the flux tower data commonly used as the target set in ML algorithms, the ability of ML to discover the inherent laws within the data is reduced. In this study, a hybrid framework was established to simulate ET in data-deficient areas. ET simulation results of a coupled model comprising the Budyko function and complementary principle (BC2021) were used as the target set of the random forest model, instead of using the flux station observation data. By combining meteorological and hydrological data, the monthly ET of the Inner Mongolia section of the Yellow River Basin (IMSYRB) was simulated from 1982 to 2020, and good results were obtained (R2 = 0.94, MAE = 3.82 mm/mon, RMSE = 5.07 mm/mon). Furthermore, the temporal and spatial variations in ET and the influencing factors were analysed. In the past 40 years, annual ET in the IMSYRB ranged between 241.38 mm and 326.37 mm, showing a fluctuating growth trend (slope = 0.80 mm/yr), and the summer ET accounted for the highest proportion in the year. Spatially, ET in the IMSYRB showed a regular distribution of high ET in the eastern region and low ET in the western area. The high ET value areas gradually expanded from east to west over time, and the area increased continuously, with the largest increase observed in the 1980s. Temperature, precipitation, and normalized difference vegetation index (NDVI) were found to be the most important factors affecting ET in the region and play a positive role in promoting ET changes. These results provide an excellent example of long-term and large-scale accurate ET simulations in an area with sparse flux stations.
Mission of Daring: The General-Purpose Heat Source Radioisotope Thermoelectric Generator

The general-purpose heat source radioisotope thermoelectric generator (GPHS-RTG), which was most recently flown on the New Horizons mission to Pluto, was originally conceived in 1979 and executed in a crash program to replace another RTG for the planned International Solar Polar Mission (ISPM). ISPM would later morph into the Ulysses mission to explore the polar regions of the Sun. When the benefits of the GPHS-RTG technology became apparent, the Galileo program also adopted the GPHS-RTG as the power source for orbital exploration of Jupiter. The GPHS-RTG then became the power source of choice for the Cassini mission to Saturn. The GPHS-RTG was designed such that it could produce 300 We at fueling with a mass of 55.9 kg, making the GPHS-RTG the most powerful RTG with the highest specific power ever flown.
A Novel Partial Decode-and-Amplify NOMA-Inspired Relaying Protocol for Uplink Short-Packet Communications

A novel partial decode-and-amplify non-orthogonal multiple access-inspired relaying (PDANR) protocol is proposed for uplink cooperative short-packet communication systems. Closed-form expressions for the average block-error-rate (BLER) of two cell-edge users are derived, based on which an asymptotic BLER expression is deduced to reveal valuable engineering insights into system design, including the transmit power and the number of antenna settings at a relay and a base station. Compared to conventional amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols, the proposed PDANR protocol achieves superior BLER performance, particularly by saving considerable transmit power. Numerical results reveal two important observations: (i) there exists an optimal performance value when the distances between the relay and the users are approximately equal; and (ii) increasing users’ block length enhances the system’s overall BLER considerably.
Molecular Apomorphies in the Secondary and Tertiary Structures of Length-Variable Regions (LVRs) of 18S rRNA Shed Light on the Systematic Position of the Family Thaumastellidae (Hemiptera: Heteroptera: Pentatomoidea)

The SSU nrDNA, a small subunit of the nuclear ribosomal DNA (coding 18S rRNA), is one of the most frequently sequenced genes in molecular studies in Hexapoda. In insects, including true bugs (Hemiptera: Heteroptera), only its primary structures (i.e., aligned sequences) are predominantly used in phylogenetic reconstructions. It is known that including RNA secondary structures in the alignment procedure is essential for improving accuracy and robustness in phylogenetic tree reconstruction. Moreover, local plasticity in rRNAs might impact their tertiary structures and corresponding functions. To determine the systematic position of Thaumastellidae within the superfamily Pentatomoidea, the secondary and—for the first time among all Hexapoda—tertiary structures of 18S rRNAs in twelve pentatomoid families were compared and analysed. Results indicate that the shapes of the secondary and tertiary structures of the length-variable regions (LVRs) in the 18S rRNA are phylogenetically highly informative. Based on these results, it is suggested that the Thaumastellidae is maintained as an independent family within the superfamily Pentatomoidea, rather than as a part of the family Cydnidae. Moreover, the analyses indicate a close relationship between Sehirinae and Parastrachiidae, expressed in morpho-molecular synapomorphies in the predicted secondary and tertiary structures of the length-variable region L (LVR L).
Continuous Safety Assessment of Updated Supervised Learning Models in Shadow Mode

Over-The-Air (OTA) updates play an essential role in the lifecycle management of modern Cyber Physical Systems (CPSs). They are deployed in short time periods to fix bugs and introduce new features. However, an important part of these updates affects safety-critical functions, and thus, requires thorough verification and validation. Particular care must be taken when using machine learning algorithms, for which it is more difficult to test all conceivable corner cases during the development process. To prevent potential unforeseen misbehavior after deployment, we introduce a method for runtime evaluation of updates in shadow mode using contract specifications. The method focuses on supervised learning models and is embedded in a workflow for iterative training. This enables carrying out reliable field testing and obtaining a realistic evaluation of the planned updates before release. Finally, we evaluate our approach on a prototype Electronic Control Unit (ECU) implementing an automotive Lane Keep Assist (LKA) system.
Miniaturized Compact Reconfigurable Half-Mode SIW Phase Shifter with PIN Diodes

In this work, a novel electrically reconfigurable phase shifter based on a half-mode substrate integrated waveguide (HM-SIW) is proposed. SIW is a guided transmission line topology, and by using half-mode excitation, a smaller size can be achieved. Phase shifters are electronic devices that change the phase of transmission for a wide range of applications, including inverse scattering and sensing. The tunability of PIN diodes is applied here to achieve a reconfigurable design. The proposed single-layer structure does not require extra wiring layers for the bias circuit on the suggested printed circuit board. Its principle consists in the integration, in the HM-SIW, of three parallel lines, each connecting the edge of the HM-SIW and linked to a PIN diode and a radial stub. Here we present the results of measurements for a frequency band from 4.5 to 7 GHz that demonstrate how the experiment agrees with simulations. Insertion loss was less than −10 dB, and port coupling was less than −2 dB for both simulation and measurement solutions. The proposed half-mode structure is around half the size of a typical SIW line. With the proposed design, the seven states of the PIN diodes can be validated (ON and OFF), with a wide band adaptation and a relatively constant phase difference across a broad frequency range (44%). A key benefit of the proposed design for a microwave component is the reduction of extra biasing layers for the PIN diodes. This is in addition to the reduced size of the transmission line compared to a commercial SIW. In the annexed section, simulation software is used for a more comprehensive analysis involving more phase shift values and parametric studies.
Energy-Based Stabilization of Forced Hamiltonian Systems and Its Application to Power Systems

The purpose of this paper is twofold. First of all, the stabilization of excitation control of power systems is considered. The system has been formulated as a forced Hamiltonian system with dissipation. The energy-based Lyapunov function is constructed to investigate the stability of the forced system. Secondly, the model of the generalized Hamiltonian systems is proposed, which consists of externally supplied energy, dissipation and internal energy source. The state space is described as a manifold equipped with a quadratic tensor field. Global coordinate free model of the generalized Hamiltonian systems is obtained.
Dengue as a Disease Threatening Global Health: A Narrative Review Focusing on Latin America and Brazil

Arboviruses constitute the largest known group of viruses. These viruses are the etiological agents of pathologies known as arboviruses, with dengue being one of the most prevalent. Dengue has resulted in important socioeconomic burdens placed on different countries around the world, including those in Latin America, especially Brazil. Thus, this work intends to carry out a narrative-based review of the literature, conducted using a study of the secondary data developed through a survey of scientific literature databases, and to present the situation of dengue, particularly its distribution in these localities. Our findings from the literature demonstrate the difficulties that managers face in controlling the spread of and planning a response against dengue, pointing to the high cost of the disease for public coffers, rendering the resources that are already limited even scarcer. This can be associated with the different factors that affect the spread of the disease, including ecological, environmental, and social factors. Thus, in order to combat the disease, it is expected that targeted and properly coordinated public policies need to be adopted not only in specific localities, but also globally.
Bell Labs and the ‘neural’ network, 1986–1996

Abstract Between 1986 and 1996 researchers at the AT&T Bell Laboratories Adaptive Systems Research Department curated thousands of images of handwritten digits assembled by the United States Postal Service to train and evaluate artificial neural networks. In academic papers and conference literature, and in conversations with the press, Bell Labs researchers, executives and company spokespeople deployed the language of neurophysiology to position the systems as capable of codifying and reproducing feats of perception. Interpretations such as these were pivotal to the formation of brain–computer imaginaries that surrounded the development of the systems, which obscured the institutional infrastructures, clerical and cognitive labour, and the manipulation and maintenance of data on which feats of ‘recognition’ depended. Central to building the group's networks was the development of data sets constructed in consort with the US Postal Service, which arbitrated between the practicality of conducting research and the representation of an extensive catalogue of possible forms and permutations of handwritten digits. These imaginaries, which stressed a likeness with the human brain, were compounded by the promotion of ‘successful applications’ that took place under the AT&T corporate umbrella and with the essential support of US Postal Service workers to correct system errors.
Cefazolin vs Second-line Antibiotics for Surgical Site Infection Prevention After Total Joint Arthroplasty Among Patients With a Beta-lactam Allergy

Abstract Background Cefazolin is a first-line agent for prevention of surgical site infections (SSIs) after total joint arthroplasty. Patients labeled allergic to beta-lactam antibiotics frequently receive clindamycin or vancomycin perioperatively due to the perceived risk of a hypersensitivity reaction after exposure to cefazolin. Methods This single-system retrospective review included patients labeled allergic to penicillin or cephalosporin antibiotics who underwent a primary total hip and/or knee arthroplasty between January 2020 and July 2021. A detailed chart review was performed to compare the frequency of SSI within 90 days of surgery and interoperative hypersensitivity reactions (HSRs) between patients receiving cefazolin and patients receiving clindamycin and/or vancomycin. Results A total of 1128 hip and/or knee arthroplasties from 1047 patients were included in the analysis (cefazolin n = 809, clindamycin/vancomycin n = 319). More patients in the clindamycin and/or vancomycin group had a history of cephalosporin allergy and allergic reactions with immediate symptoms. There were fewer SSIs in the cefazolin group compared with the clindamycin and/or vancomycin group (0.9% vs 3.8%; P < .001) including fewer prosthetic joint infections (0.1% vs 1.9%). The frequency of interoperative HSRs was not different between groups (cefazolin = 0.2% vs clindamycin/vancomycin = 1.3%; P = .06). Conclusions The use of cefazolin as a perioperative antibiotic for infection prophylaxis in total joint arthroplasty in patients labeled beta-lactam allergic is associated with decreased postoperative SSI without an increase in interoperative HSR.
MENTA: how to balance authorial intention and user agency in virtual environments

We aim to create an artificial intelligence based virtual environment to train medical team leaders to rescue injured people after a mass casualty. In this paper, we describe a resilient and adaptive engine, MENTA, to orchestrate dynamically various training situations and various virtual teammates. MENTA is in charge of the narrative control by proposing a set of adjustments that satisfies narrative objectives chosen by the trainer. These adjustments take the form of a prescribed scenario that is generated by MENTA via a planning engine that we have coupled with fuzzy cognitive maps. This approach tackles the problem of a set of objectives that are often contradictory: user agency, authorial intention and resilience.
Contributions to the Cell Growth Problem

The cell growth problem is a combinatorial problem which may be stated as follows: A plane animal is made up of cells, each of which is a square of unit area. It starts as a single cell, and grows by adding cells one at a time in such a way that the new cell has at least one side in contact with a side of a cell already present in the animal. The problem is to find the number of different animals of area n, it being understood that animals which can be transformed into each other by reflections or rotations of the plane will be regarded as the same animal.
An Empirical Study of Pre-Trained CNN Models on COVID-19 CT Scan Images

As COVID-19 is highly infectious, the prevention of this disease is mandatory. The instant diagnosis of this disease is obligatory to stop the infection. The most commonly used procedure for COVID-19 detection is the RT-PCR test. But this process is very time-consuming and as a result, it allows the covid infected persons to spread the infection before they come to know the test result. So, in this paper, we used the method of detecting COVID-19 from CT scan images as a replacement for the conventional RT-PCR test. But this alternative method has its demerit too. To diagnose COVID-19 from these CT scan images, the analysis of a radiologist expert is required. So, we have used a deep-learning based method for automatic detection of covid infection from the CT scan images. We have used six pre-trained models: ResNet50, Xception, DenseNet121, DenseNet201, MobileNet, MobileNetV2 and their accuracy are 97.38%, 92.35%, 95.56%, 93.55%, 93.95%, and 92.94% respectively.
The Rate of Postoperative Mortality and Renal and Respiratory Complications are Increased in Patients with Extreme Obesity Undergoing Cardiac Surgery – A Retrospective Observational Cohort Study of 8848 Patients

Introduction The importance of obesity as a potential risk factor in open heart surgery is well known. The epidemic of extreme obesity is an increasing public health concern and raises alerts regarding postoperative complications and mortality in patients undergoing cardiac surgery. The study aimed to analyze the impact of extreme obesity (BMI≥40) on the frequency of postoperative complications, as well as early and delayed mortality compared to patients with a lower body mass. Materials and Methodology This retrospective observational cohort study involved patients, over the age of 18, undergoing cardiac surgery with cardiopulmonary bypass at the Cardiac Surgery Department of the Pomeranian Medical University in Szczecin, Poland between January 1st, 2010 and December 31st, 2018. The patients included in the study were allocated into two subgroups depending on the BMI index (Group I BMI≥40 vs Group II BMI<40). Results A total of 8848 adult patients of both genders were included. Baseline characteristics for Group I and Group II were mean age 64.07±7.76 vs 65.10±9.68 years (p=0.123), mean BMI 42.13±2.44 vs 28.55±4.23 (p<0.001), with more females in Group I (58.04% vs 29.06%) and more males in Group II (70.94% vs 29.06%), p<0.001. The predicted perioperative risk using the EuroScore Logistics scale was higher in a group with BMI≥40 (p<0.001). Regression analysis with adjustment for confounding factors showed a statistically significant relationship between BMI≥40 and postoperative respiratory failure (OR=1.760, p=0.043), acute kidney injury AKIN2 (OR=2.082, p=0.044) and AKIN3 (OR=2.743, p=0.039). 30-day mortality in the univariate analysis showed a statistically significant relationship, however, after modifying the results with interfering factors, no statistical significance was obtained. Conclusion The risk of postoperative acute respiratory failure and acute renal injury was increased in patients with BMI≥40. The probability of 30-day survival of patients after cardiac surgery was much lower in people with extreme obesity, although it was related to the dominant comorbidities. The 10-year survival was comparable in both groups.
Macrophage Involvement in Aging-Associated Skeletal Muscle Regeneration

The skeletal muscle is a dynamic organ composed of contractile muscle fibers, connective tissues, blood vessels and nerve endings. Its main function is to provide motility to the body, but it is also deeply involved in systemic metabolism and thermoregulation. The skeletal muscle frequently encounters microinjury or trauma, which is primarily repaired by the coordinated actions of muscle stem cells (satellite cells, SCs), fibro-adipogenic progenitors (FAPs), and multiple immune cells, particularly macrophages. During aging, however, the capacity of skeletal muscle to repair and regenerate declines, likely contributing to sarcopenia, an age-related condition defined as loss of muscle mass and function. Recent studies have shown that resident macrophages in skeletal muscle are highly heterogeneous, and their phenotypes shift during aging, which may exacerbate skeletal muscle deterioration and inefficient regeneration. In this review, we highlight recent insight into the heterogeneity and functional roles of macrophages in skeletal muscle regeneration, particularly as it declines with aging.
Enhanced Half-Mode SIW Loaded With Interdigital Capacitor for Permittivity Measurements

This article presents a novel sensor topology employing an interdigital capacitor (IDC) integrated into a half-mode substrate-integrated waveguide (HMSIW) for permittivity measurement of solid materials. HMSIW with around 50% smaller size compared with SIW offers a compact solution for hosting the sensing section. Capacitive-like characteristic of IDC further improves the size reduction by up to 71.6%. In addition, IDC with enhancing the electric field concentration is exploited for the sensing section. Design details of the hosting Section and the sensing Section are provided along with extraction and analysis of the equivalent circuit model of the sensor. Design and simulations are carried out by means of design tools, and the proposed sensor is fabricated on a $50\times 24\times1.6$ mm3 printed circuit board (PCB). Measurements demonstrate that the fabricated sensor prototype shows 113-MHz frequency shift per unit permittivity change around 3.5 GHz, and it has a normalized sensitivity of 3.16% within a wide range of permittivity values, which is relatively better than similar sensors in the literature.
a Compact Size FSS Unit Cell Design For UWB Filtering and Shielding Applications

In this paper, a Frequency Selective Surface (FSS) Unit Cell (UC) for UWB filtering and Shielding applications is presented. The suggested UC is designed on an FR-4 substrate with dielectric constant $\varepsilon_{r}$=4.3 with a compact size of 6 x6mm2. the designed structure operates on a very wide frequency band of14 GHz (from 2 to 16 GHz) with very high Shielding effectiveness (maximum SE of 49.2 dB at 9.9 GHz) through the same operating band. The proposed design was discussed with simulations and good results were obtained.
A Pico-Second Timing System on a Chip (SoC) for Magnetostrictive Displacement Sensors (MDSs)

Based on the Wiedemann effect, Magnetostrietive Displacement Sensors (MDSs) can measure displacement without contact so that it is free of wear. Therefore, compared with other displacement sensors, the MDSs has a longer service life and is more adaptable to harsh environments. The MDSs are getting more attention and are widely used in industry control system. Precision time interval is the key aspect of the MDSs. In this paper, a pico-second timing system on chip (SoC) is designed in a 180 nm CMOS process for the MDSs applications. SoC is proposed for the MDSs applications. The chip integrates a high speed comparator and a time-to-digital converter (TDC) to build a fine time measurement chain. A 32-MHz microcontroller unit (MCU) realized by RISC-V core with two-stage pipeline is realized for system control. Test results show that the comparator temporal noise is around 1 mV and the TDC achieves a resolution of 156 ps.