Miracle-dz/UniFAR-FTUs huggingface dataset:
Phased array antennas for mmWave frequency spectrum for 5G communication

We are currently analyzing and simulating an array of antenna with changing phases. Conventional antennas (such as parabolic reflectors) are difficult to move either in azimuth or in elevation, and require more time as they are controlled by servo motors and actuators. On the contrary, the phased array antenna utilizes electronic means to rotate the beam in desired direction. To move or rotate the beam in desired direction, phase of transmitting elements in the array are varied by a device known as phase shifter. Our research mainly focuses on obtaining results in showing that creating an array of antenna and steering the beam in a particular direction is much more efficient in comparison to the conventional method. Moreover, creating an array of antennas can help us to increase the gain compared to a single antenna and we can also move the beam in our desired direction without any mechanical movement of the antenna. Additionally, we worked to change the design of our microstrip patch array element and fruitfully created a key shaped antenna that gives substantially better performance than the original array.
Subspace Model-Assisted Deep Learning for Improved Image Reconstruction

Image reconstruction from limited and/or sparse data is known to be an ill-posed problem and a priori information/constraints have played an important role in solving the problem. Early constrained image reconstruction methods utilize image priors based on general image properties such as sparsity, low-rank structures, spatial support bound, etc. Recent deep learning-based reconstruction methods promise to produce even higher quality reconstructions by utilizing more specific image priors learned from training data. However, learning high-dimensional image priors requires huge amounts of training data that are currently not available in medical imaging applications. As a result, deep learning-based reconstructions often suffer from two known practical issues: a) sensitivity to data perturbations (e.g., changes in data sampling scheme), and b) limited generalization capability (e.g., biased reconstruction of lesions). This paper proposes a new method to address these issues. The proposed method synergistically integrates model-based and data-driven learning in three key components. The first component uses the linear vector space framework to capture global dependence of image features; the second exploits a deep network to learn the mapping from a linear vector space to a nonlinear manifold; the third is an unrolling-based deep network that captures local residual features with the aid of a sparsity model. The proposed method has been evaluated with magnetic resonance imaging data, demonstrating improved reconstruction in the presence of data perturbation and/or novel image features. The method may enhance the practical utility of deep learning-based image reconstruction.
Explicating the role of amygdala substructure alterations in the link between hypoleptinemia and rumination in anorexia nervosa

The amygdaloid complex plays a pivotal role in emotion processing and has been associated with rumination transdiagnostically. In anorexia nervosa (AN), we previously observed differential reductions of amygdala nuclei volumes (rostral‐medial cluster substantially affected) and, in another study, elevated food−/weight‐related rumination. Both amygdala volumes and rumination frequency correlated with characteristically suppressed leptin levels in AN. Thus, we hypothesized that amygdala nuclei alterations might be associated with AN‐related rumination and potentially mediate the leptin‐rumination relationship in AN.
Core temperature and heart rate at the upper limit of the prescriptive zone

The expressed goal of limiting workplace heat stress exposures to a core temperature (Tc) of 38°C traces back to a 1969 World Health Organization Technical Report (WHO Series 412). The actual goal was to limit exposures to the upper limit of the prescriptive zone (ULPZ). To explore the physiological strain at the ULPZ, progressive heat stress protocol data from Penn State University (PSU) and University of South Florida (USF) below and at the ULPZ were used to articulate the relation of Tc and heart rate (HR) to metabolic rate (MR) with consideration of acclimatization state, clothing, exposure condition (PreULPZ vs. ULPZ), and sex. Regression models demonstrated the association of MR and sex with Tc and HR. At the ULPZ, women had systematically higher values of Tc and HR than men at the same MR likely due to higher relative demands. There was no effect for acclimatization state and clothing. As expected for individuals, Tc was practically constant below the ULPZ and HR exhibited increasing values approaching the ULPZ. At 490 W, the high MR cited in the WHO document, the mean Tc for men was near the 38°C limit with systematically lower Tc at lower MRs.
A whole-task brain model of associative recognition that accounts for human behavior and neuroimaging data

Brain models typically focus either on low-level biological detail or on qualitative behavioral effects. In contrast, we present a biologically-plausible spiking-neuron model of associative learning and recognition that accounts for both human behavior and low-level brain activity across the whole task. Based on cognitive theories and insights from machine-learning analyses of M/EEG data, the model proceeds through five processing stages: stimulus encoding, familiarity judgement, associative retrieval, decision making, and motor response. The results matched human response times and source-localized MEG data in occipital, temporal, prefrontal, and precentral brain regions; as well as a classic fMRI effect in prefrontal cortex. This required two main conceptual advances: a basal-ganglia-thalamus action-selection system that relies on brief thalamic pulses to change the functional connectivity of the cortex, and a new unsupervised learning rule that causes very strong pattern separation in the hippocampus. The resulting model shows how low-level brain activity can result in goal-directed cognitive behavior in humans.
Examining the relationship between maternal body size, gestational glucose tolerance status, mode of delivery and ethnicity on mother’s milk microbiota at three months post-partum

Background: Few studies have examined how maternal body mass index (BMI), mode of delivery and ethnicity affect the microbial composition of human milk and none have examined associations with maternal metabolic status. Given the high prevalence of maternal adiposity and impaired glucose metabolism, and the importance of human milk in the colonization of the infant gut, we systematically investigated the associations between these maternal factors and milk microbial composition and functionality. Methods: Women ≥20 years were recruited during pregnancy and milk samples were collected at 3 months post-partum (NCT01405547). Demographic data, weight, height, and a 3-hour oral glucose tolerance test were conducted at 30 (95% CI: 25-33) weeks gestation. Metagenomic DNA extraction and 16S ribosomal RNA gene sequencing of the V4 hypervariable region (Illumina MiSeq) was carried out on 113 milk samples. Results: Multivariable linear regression analyses demonstrated no significant associations between maternal characteristics (maternal BMI [pre-pregnancy, 3 months post-partum], glucose tolerance, mode of delivery and ethnicity) and microbiota alpha-diversity; however, pre-pregnancy BMI was associated with human milk beta-diversity (Bray-Curtis p=0.040). Women with a pre-pregnancy BMI >30 kg/m2 (obese) had a greater incidence of Bacteroidetes (incidence rate ratio [IRR]: 3.70 [95% CI: 1.61-8.48]) and a reduced incidence of Proteobacteria (0.62 [0.43-0.90]), compared to overweight women (BMI 25.0-29.9 kg/m2) as assessed by multivariable Poisson regression. Increased incidence of Gemella was observed among overweight (versus healthy) mothers with gestational diabetes (5.96 [1.85-19.21]) and obese (versus healthy) mothers with impaired glucose tolerance (4.04 [1.63-10.01]). An increased incidence of Brevundimonas (16.70 [5.99-46.57]) was found in the milk of women who underwent an unscheduled C-section versus vaginal delivery. Lastly, functional gene inference demonstrated that obesity was associated with increased abundance of genes encoding for the biosynthesis of secondary metabolites in milk (coefficient=0.00028, p=0.0070). Conclusions: Mother’s milk has a diverse microbiota of which its diversity and differential abundance appear associated with maternal body size, glucose tolerance status, mode of delivery, and ethnicity. Further research is warranted to determine whether this variability in the milk microbiota impacts colonization of the infant gut.
The efficacy of inspiratory muscle training in patients with coronary artery disease: Protocol for a systematic review and meta-analysis

Background Inspiratory muscle training (IMT) has been recognized as an effective form of training in patients with cardiovascular disease and heart failure. However, little is known about the efficacy of IMT in the treatment of patients with coronary artery disease (CAD). The aim of this systematic review will be to evaluate randomized controlled studies to understand the effect of IMT on CAD patients. Method We will include randomized controlled trials evaluating the efficacy of IMT in patients 18 years and older diagnosed with CAD. Crossover trials, cluster-randomized, quasi-randomized, and non-randomized trials will be excluded. Study search will be conducted in major databases (MEDLINE, the Cochrane Central Register of Controlled Trials, Embase, and PEDro). The study intervention will be IMT independent of the duration, frequency, or intensity of training. The primary outcome will be quality of life, patient-reported health status, and all adverse events related to IMT. Secondary outcomes will include exercise capacity and respiratory muscle strength. The risk of bias will be evaluated based on the Cochrane Risk of Bias tool. Screening, data extraction, and quality assessment will be performed by two independent reviewers. If two or more studies are considered to be clinically homogeneous, a meta-analysis based on the random-effects model will be performed. The quality of evidence will be evaluated based on the GRADE approach. Conclusion This systematic review will improve our understanding of the effects of IMT on CAD patients and potentially establish IMT as an alternative form of exercise training for the treatment of CAD. Trial registration Study registration. OSF registries (https://osf.io/3ch7m). Date registered: May 10, 2022. Registration DOI: https://doi.org/10.17605/OSF.IO/GVMY7.
Injectable Decorin/Gellan Gum Hydrogel Encapsulating Adipose-Derived Stem Cells Enhances Anti-Inflammatory Effect in Cartilage Injury via Autophagy Signaling

Adipose-derived stem cells (ADSCs) are employed as a promising alternative in treating cartilage injury. Regulating the inflammatory “fingerprint” of ADSCs to improve their anti-inflammatory properties could enhance therapy efficiency. Herein, a novel injectable decorin/gellan gum hydrogel combined with ADSCs encapsulation for arthritis cartilage treatment is proposed. Decorin/gellan gum hydrogel was prepared according to the previous manufacturing protocol. The liquid–solid form transition of gellan gum hydrogel is perfectly suitable for intra-articular injection. Decorin-enriched matrix showing an immunomodulatory ability to enhance ADSCs anti-inflammatory phenotype under inflammation microenvironment by regulating autophagy signaling. This decorin/gellan gum/ADSCs hydrogel efficiently reverses interleukin-1β-induced cellular injury in chondrocytes. Through a mono-iodoacetate-induced arthritis mice model, the synergistic therapeutic effect of this ADSCs-loaded hydrogel, including inflammation attenuation and cartilage protection, is demonstrated. These results make the decorin/gellan gum hydrogel laden with ADSCs an ideal candidate for treating inflammatory joint disorders.
Examination of ELISA against PCR for assessing treatment efficacy against Cryptosporidium in a clinical trial context

Background Cryptosporidium is a gastrointestinal pathogen that presents a serious opportunistic infection in immunocompromised individuals including those living with human immunodeficiency syndrome. The CRYPTOFAZ trial, previously published, was conducted in Malawi to evaluate the efficacy of clofazimine in response to an unmet need for drugs to treat cryptosporidiosis in HIV populations. A combination of rapid diagnostic tests, ELISA, qPCR, and conventional sequencing were employed to detect Cryptosporidium in 586 individuals during pre-screening and monitor oocyst shedding and identify enteric co-pathogens in 22 enrolled/randomized participants during the in-patient period and follow-up visits. Methodology Oocyst shedding as measured by qPCR was used to determine primary trial outcomes, however pathogen was detected even at trial days 41–55 in individuals randomized to either clofazimine or placebo arms of the study. Therefore, in this work we re-examine the trial outcomes and conclusions in light of data from the other diagnostics, particularly ELISA. ELISA data was normalized between experiments prior to comparison to qPCR. The amount of all identified enteric pathogens was examined to determine if co-pathogens other than Cryptosporidium were major causative agents to a participant’s diarrhea. Conclusion ELISA had higher sample-to-sample variability and proved to be equally or less sensitive than qPCR in detecting Cryptosporidium positive samples. Compared to qPCR, ELISA had equal or greater specificity in detecting Cryptosporidium negative samples. Sequencing identified several Cryptosporidium species including viatorum which has never been identified in Malawi and Southern Africa. In addition to Cryptosporidium, enterotoxigenic E. coli was also identified as a pathogen in diarrheagenic amounts in 4 out of 22 participants.
The relationship between age and sex partner counts during the mpox outbreak in the UK, 2022

Background Understanding the dynamics of an infectious disease outbreak linked to sexual activity requires valid expectations of likely counts of unique sex partners during the infectious period. Typically, age is the key demographic trait linked to expected partner count, with many transmission models removing adults from the sexually active pool abruptly at a pre-specified age threshold. Modelling the rate of decline in partner counts with age would benefit from a better description of empirical evidence. Methods During the 2022 mpox epidemic in the UK, we asked individuals about their partner counts in the preceding three weeks, which is about the same as usual infectious period for persons with active mpox. We used negative binomial regression (all responses) and Weibull regression (non-zero responses) to analyse the relationship between age and partner counts, adjusted for other demographic data (such as education level and occupation), sub-dividing by three types of respondent: men who have sex with men (MSM), men who have sex with women, and women who have sex with men. Results Most respondents had zero or one recent partner, all distributions were skewed. There was a relatively linear declining relationship between age and partner counts for heterosexual partnership groups, but a peak in partner counts and concurrency for MSMs in middle age years (age 35–54), especially for MSM who seemed to be in a highly sexually active subgroup. Conclusion Useful data were collected that can be used to describe sex partner counts during the British mpox epidemic and that show distinctive partner count relationships with age, dependent on partnership type.
Intact mitochondrial function in the setting of telomere‐induced senescence

Mitochondria play essential roles in metabolic support and signaling within all cells. Congenital and acquired defects in mitochondria are responsible for several pathologies, including premature entrance to cellar senescence. Conversely, we examined the consequences of dysfunctional telomere‐driven cellular senescence on mitochondrial biogenesis and function. We drove senescence in vitro and in vivo by deleting the telomere‐binding protein TRF2 in fibroblasts and hepatocytes, respectively. Deletion of TRF2 led to a robust DNA damage response, global changes in transcription, and induction of cellular senescence. In vitro, senescent cells had significant increases in mitochondrial respiratory capacity driven by increased cellular and mitochondrial volume. Hepatocytes with dysfunctional telomeres maintained their mitochondrial respiratory capacity in vivo, whether measured in intact cells or purified mitochondria. Induction of senescence led to the upregulation of overlapping and distinct genes in fibroblasts and hepatocytes, but transcripts related to mitochondria were preserved. Our results support that mitochondrial function and activity are preserved in telomere dysfunction‐induced senescence, which may facilitate continued cellular functions.
Effects of Intraoperative Cochlear Implant Electrode Conditioning on Impedances and Electrically Evoked Compound Action Potentials

Objective: The current study investigates whether, during a Cochlear Implant (CI) surgery, conditioning (i.e. applying short bursts of electrical stimulation) within a saline solution can have positive effects on subsequent intra-operative measurements. We hypothesize that, based on previous research, the impedance values will be reduced, and that the reproducibility of Electrically Evoked Compound Action Potentials (ECAPs) is improved as a result of conditioning. Methods: We conditioned half of the electrode contacts, within a saline solution, before CI insertion, using 23 MED-EL implants. Impedance was measured for both the conditioned and non-conditioned groups at five time points. Repeated ECAP recordings were measured and compared between the conditioned and non-conditioned groups. Results: Impedance of the electrode contacts were reduced by 31% after conditioning in saline solution; however, there were no clinically relevant differences after the implantation of the electrode array. The hypothesis that measurement reproducibility would be increased after conditioning could not be confirmed with our data. Within the saline solution, we observed that 44% of the electrode contacts were covered with air bubbles, which most disappeared after implantation. However, these air bubbles limited the effectiveness of the conditioning within the saline solution. Lastly, the effect of conditioning on the reference electrode stimulation was approximately 16% of the total reduction in impedance. Conclusion: Our data does not suggest that intraoperative conditioning is clinically required for cochlear implantation with MED-EL implants. Additionally, an in-vivo ECAP recording can be considered as a method of conditioning the electrode contacts. Significance: We confirm that the common clinical practice does not need to be changed.
Application of Molecular Dynamics Simulations to Plasma Etch Damage in Advanced Metal-Oxide-Semiconductor Field-Effect Transistors

According to "the international technology roadmap for semiconductors (ITRS)" (SIA, 2009), the shrinkage of silicon-based metal–oxide–semiconductor field-effect transistor (MOSFET) – an elemental device (unit) in ultra-large-scale integrated (ULSI) circuits – has been accelerating due to expanding demands for the higher performance and the lower power operation. The characteristic dimensions of current MOSFETs in mass productions are around 30 – 50 nm. Figure 1 shows the scaling trend of the key feature sizes in ULSI circuits predicted by Semiconductor Industry Association, USA. Various types of MOSFETs are designed for the specific purposes, i.e., low standby power (LSP), low operation power (LOP), and high performance (HP) operations, and built in ULSI circuits such as dynamic random access memory (DRAM) and micro-processing unit (MPU). New structured MOSFETs such as fully-depleted (FD) and metal-gate (MG) devices have been recently proposed. Since physical gate length (Lg) and source / drain extension depth (Ext) are the key feature sizes determining MOSFET performance (Sze & Ng, 2007), the shrinkage of Lg and Ext is a primal focus in the development of MOSFETs. These sizes have become a few nanometers, comparable to the scale of atomistic simulation domain.
Communication of Uncertainty Information in Cooperative, Automated Driving: A Comparative Study of Different Modalities

Cooperation between drivers and automated vehicles requires transparent communication of the automation’s current status. This can be achieved by communicating confidence or certainty in its current perception or decision. We evaluate different sensory modalities for communicating information about how safely an automated driving system can perform the driving task in critical traffic situations to a driver who is present as a cooperator. We aimed to improve communication between the driving system and the human driver, ultimately increasing the overall driving experience and performance. In a virtual reality driving simulation study with 34 participants, we presented confidence information across three modalities: visual, auditory, and vibrotactile, compared to a baseline condition. Our results indicate that communicating automation uncertainty through the auditory and vibrotactile modalities improved user experience, trust in automation, and perceived safety. At the same time, interactions with the Non-Driving Related Task were reduced by communicating confidence information in critical driving situations.
ARcoustic: A Mobile Augmented Reality System for Seeing Out-of-View Traffic

Locating out-of-view vehicles can help pedestrians to avoid critical traffic encounters. Some previous approaches focused solely on visualising out-of-view objects, neglecting their localisation and limitations. Other methods rely on continuous camera-based localisation, raising privacy concerns. Hence, we propose the ARcoustic system, which utilises a microphone array for nearby moving vehicle localisation and visualises nearby out-of-view vehicles to support pedestrians. First, we present the implementation of our sonic-based localisation and discuss the current technical limitations. Next, we present a user study (n = 18) in which we compared two state-of-the-art visualisation techniques (Radar3D, CompassbAR) to a baseline without any visualisation. Results show that both techniques present too much information, resulting in below-average user experience and longer response times. Therefore, we introduce a novel visualisation technique that aligns with the technical localisation limitations and meets pedestrians’ preferences for effective visualisation, as demonstrated in the second user study (n = 16). Lastly, we conduct a small field study (n = 8) testing our ARcoustic system under realistic conditions. Our work shows that out-of-view object visualisations must align with the underlying localisation technology and fit the concrete application scenario.