Miracle-dz/UniFAR-FTUs huggingface dataset:
The Efficacy and Safety of a Low-Fluence 1064 nm Picosecond ND-YAG Laser Compared with Those of a Low-Fluence Photoacoustic Therapy Pulsed (PTP) Mode 1064 nm Q-Switched ND-YAG Laser for Treatment of Melasma: A Prospective Split-Face Study

Melasma is a challenging pigmentation disorder to treat, and although low-fluence 1064 nm picosecond ND-YAG lasers have shown potential for treating benign pigmented disorders, data on the use of this laser for melasma treatment are currently insufficient. In this prospective split-face study, twenty-four patients with melasma on the face were enrolled and randomly assigned to receive treatment on one side of the face either with a low-fluence 1064 nm picosecond ND-YAG laser or with a low-fluence PTP mode 1064 nm Q-switched ND-YAG laser. Laser treatment was performed 5 times at intervals of 2 weeks, with evaluation conducted before each treatment and 2 months after the completion of 5 treatments. Clinical pictures using a standardized, digital photographic system and dermoscopy were taken on each day of the visit. The modified melasma area severity index (mMASI), melanin index (MI), dermoscopic scores of the pigmentary and vascular elements in melasma, pain during laser treatment, and patient satisfaction score were recorded. Twenty-one participants completed the study, and from week 2 in both groups, a significant decrease in mMASI and MI were confirmed. Although no statistically significant difference was observed, the decrease in mMASI and MI were greater in the 1064 nm picosecond ND-YAG laser group than in the 1064 nm Q-switched ND-YAG laser group. The 1064 nm picosecond ND-YAG laser group showed significant improvement in the pseudoreticular network and globular pattern of dermoscopic features between week 0 and week 16, while significant improvement in the globular pattern was shown in the 1064 nm Q-switched ND-YAG laser group. No significant difference was observed between the two groups in terms of the patient satisfaction score and pain during laser treatments. Notably, no adverse events were observed in either group. In conclusion, our study demonstrated that a low-fluence 1064 nm picosecond ND-YAG laser is as effective and safe in the treatment of melasma as a low-fluence PTP mode 1064 nm Q-switched ND-YAG laser.
Detection of Merkel Cell Polyomavirus (MCPyV) DNA and Transcripts in Merkel Cell Carcinoma (MCC)

Merkel cell polyomavirus (MCPyV) is the etiological agent of the majority of Merkel cell carcinoma (MCC): a rare skin tumor. To improve our understanding of the role of MCPyV in MCCs, the detection and analysis of MCPyV DNA and transcripts were performed on primary tumors and regional lymph nodes from two MCC patients: one metastatic and one non-metastatic. MCPyV-DNA was searched by a quantitative polymerase chain reaction (qPCR), followed by the amplification of a Large T Antigen (LTAg), Viral Protein 1 (VP1) and Non-Coding Control Region (NCCR). LTAg and VP1 transcripts were investigated by reverse-transcription PCR (RT-PCR). Viral integration was also studied, and full-length LTAg sequencing was performed. qPCR revealed that the primary tumor of both patients and the lymph node of one patient was positive for the small t-antigen, with an average value of 7.0 × 102 copies/µg. The same samples harbored LTAg, NCCR and VP1 DNA. Sequencing results showed truncated LTAg with the conserved retinoblastoma (Rb) protein binding motif and VP1 and NCCR sequences identical to the MCC350 strain. RT-PCR detected LTAg but not VP1 transcripts. The MCPyV genome was integrated into the primary tumor of both patients. The results confirmed the connection between MCPyV and MCC, assuming integration, LTAg truncation and Rb sequestration as key players in MCPyV-mediated oncogenesis.
“I Keep Sweet Cats In Real Life, But What I Need In The Virtual World Is A Neurotic Dragon”: Virtual Pet Design With Personality Patterns

A BSTRACT Virtual Pets serve as companionships and meaningful in-game narratives in the metaverse. Players have unique personalities and personality preferences for their pets. However, the design of virtual pets often relies on designers’ individual experiences without considering the virtual pets’ personalities. We designed the virtual pets’ visual appearances by following the design guidelines from the Five Factor Model (FFM) in voxel format. We conducted a study to investigate people’s perceptions of virtual pets’ personalities and appearances through two user studies. Our findings suggest that voxel-style virtual pets better represented agreeableness than realistic pet pictures. Additionally, users prefer virtual pets (voxel-style pets generated with machine-learning techniques) that share similar personalities. The study’s results provide valuable insights for game designers and researchers for future pet game design and understanding of how people perceive virtual pets based on their appearance and behavior.
Propagation of singularities for linearised hybrid data impedance tomography

For a general formulation of linearised hybrid inverse problems in impedance tomography, the qualitative properties of the solutions are analysed. Using an appropriate scalar pseudo-differential formulation, the problems are shown to permit propagating singularities under certain non-elliptic conditions, and the associated directions of propagation are precisely identified relative to the directions in which ellipticity is lost. The same result is found in the setting for the corresponding normal formulation of the scalar pseudo-differential equations. A numerical reconstruction procedure based of the least squares finite element method is derived, and a series of numerical experiments visualise exactly how the loss of ellipticity manifests itself as propagating singularities.
Parameterizing eddy form stress in a thickness-weighted average isopycnal ocean model

Mesoscale eddies are unresolved in most of today’s global ocean models, and their effect on the large-scale ocean circulation needs to be parameterized. Greatbatch and Lamb (1990, GL90) suggested an eddy form stress parameterization that mixes geostrophic momentum in the vertical. The GL90 vertical viscosity scheme, which is equivalent to the Gent and McWilliams (1990, GM90) parameterization under the geostrophic assumption, has seen only very limited use, and exclusively in models that use z-coordinates and are of very coarse resolution. In this paper, we explore the GL90 parameterization in an idealized isopycnal coordinate model, both from a theoretical and practical perspective. We further compare the effects of the GM90 and GL90 parameterizations across a range of non-eddying to eddy-permitting resolutions. From a theoretical perspective, the GL90 parameterization is more attractive than the GM90 scheme for isopycnal coordinate models because GL90 provides an interpretation that is fully consistent with thickness-weighted isopycnal averaging, while GM90 cannot be entirely reconciled with any fully isopycnal averaging framework. From a practical perspective, the GL90 and GM90 parameterizations lead to extremely similar energy levels, flow and vertical structure, even though their energetic pathways are very different. The equivalence holds true from non-eddying through eddy-permitting resolution. We conclude that in isopycnal coordinate models, the GL90 parameterization provides a good–if not equivalent–alternative to the GM90 parameterization. The GL90 parameterization is more advantageous in terms of computational efficiency, ease of implementation, and numerical stability.
H influenzae & M catarrhalis in sputum of severe asthma with inflammasome and neutrophil activation

Background. Because of altered airway microbiome in asthma, we analysed the bacterial species in sputum of patients with severe asthma. Methods. Whole genome sequencing was performed on induced sputum from non-smoking (SAn) and current or ex-smoker (SAs/ex) severe asthma patients, mild/moderate asthma (MMA) and healthy controls (HC). Data was analysed by asthma severity, inflammatory status and transcriptome-associated clusters (TACs). Results. α-diversity at the species level was lower in SAn and SAs/ex, with an increase in Haemophilus influenzae and Moraxella catarrhalis, and Haemophilus influenzae and Tropheryma whipplei, respectively, compared to HC. In neutrophilic asthma, there was greater abundance of Haemophilus influenzae and Moraxella catarrhalis and in eosinophilic asthma, Tropheryma whipplei was increased. There was a reduction in α-diversity in TAC1 and TAC2 that expressed high levels of Haemophilus influenzae and Tropheryma whipplei, and Haemophilus influenzae and Moraxella catarrhalis, respectively, compared to HC. Sputum neutrophils correlated positively with Moraxella catarrhalis and negatively with Prevotella, Neisseria and Veillonella species and Haemophilus parainfluenzae. Sputum eosinophils correlated positively with Tropheryma whipplei which correlated with pack-years of smoking. αand βdiversities were stable at one year. Conclusions. Haemophilus influenzae and Moraxella catarrhalis were more abundant in severe neutrophilic asthma and TAC2 linked to inflammasome and neutrophil activation, while Haemophilus influenzae and Tropheryma whipplei were highest in SAs/ex and in TAC1 associated with highest expression of IL-13 Type 2 and ILC2 signatures with the abundance of Tropheryma whipplei correlating positively with sputum eosinophils. Whether these bacterial species drive the inflammatory response in asthma needs evaluation. H influenzae & M catarrhalis in sputum of severe asthma with inflammasome and neutrophil activation Ali Versi, Fransiskus Xaverius Ivan, Mahmoud I Abdel-Aziz, Stewart Bates, John Riley, Frederic Baribaud, Nazanin Zounemat Kermani, Paolo Montuschi, Sven-Erik Dahlen, Ratko Djukanovic, Peter
Hidden magma system causing intense earthquake swarm in the northeastern Noto Peninsula, Japan

An intense earthquake swarm is occurring in the crust of the northeastern Noto Peninsula, Japan. Fluid movement related to volcanic activity is often involved in earthquake swarms in the crust, but the last volcanic activity in this area occurred in the middle Miocene (15.6 Ma), and no volcanic activity has occurred since then. In this study, we investigated the cause of this earthquake swarm using spatiotemporal variation of earthquake hypocenters and seismic reflectors. Hypocenter relocation revealed that earthquakes moved from deep to shallow areas via many planes, similar to earthquake swarms in volcanic regions. The strongest M5.4 earthquake initiated near the migration front of the hypocenters. Moreover, it ruptured the seismic gap between the two different clusters. The initiation of this earthquake swarm occurred at a locally deep depth (z = ̃17 km), and we found a distinctive S-wave reflector, suggesting a fluid source in the immediate vicinity. The local hypocenter distribution revealed a characteristic ring-like structure similar to the ring dike that forms just above the magma reservoir and is associated with caldera collapse and/or magma intrusion. These observations suggest that the current seismic activity was impacted by fluids related to ancient or present hidden magmatic activity, although no volcanic activity was reported. Significant crustal deformation was observed during this earthquake swarm, which may also be related to fluid movement and contribute to earthquake occurrences. A seismic gap zone in the center of the swarm region may represent an area with aseismic deformation.
A two-parameter learnable Logmoid Activation Unit

A novel learnable Logmoid Activation Unit (LAU) is proposed as, f(x) = x ln(1+αSigmoid(βx)), by parameterizing Sigmoid with two hyper-parameters α and β that are optimized by the back-propagation algorithm. The end-to-end deep neural networks with learnable LAUs can increase the predictive performances beyond well-known activation functions for different tasks.
A Novel Deep Learning Approach for Data Assimilation of Complex Hydrological Systems

In hydrological research, data assimilation (DA) is widely used to fuse the information contained in process‐based models and observational data to reduce simulation uncertainty. However, many popular DA methods are limited by low computational efficiency or their reliance on the Gaussian assumption. To address these limitations, we propose a novel DA method called DA(DL), which leverages the capabilities of DL to model non‐linear relationships and recognize complex patterns. DA(DL) first generates a large volume of training data from the prior ensemble, and then trains a DL model to update the system knowledge (e.g., model parameters in this study) from multiple predictors. For highly non‐linear models, an iterative form of DA(DL) can be implemented. Additionally, strategies of data augmentation and local updating are proposed to enhance DA(DL) for problems involving small ensemble size and the equifinality issue, respectively. In two hydrological DA cases involving Gaussian and non‐Gaussian distributions, DA(DL) shows promising performance compared to two ensemble smoother methods, that is, ES(K) and ES(DL), which respectively apply the Kalman‐ and DL‐based updates. Potential improvements to DA(DL) can be made by designing better DL model architectures, imposing physical constraints to the training of the DL model, and further updating other important variables like model states, forcings and error terms.
Reevaluating Data Partitioning for Emotion Detection in EmoWOZ

This paper focuses on the EmoWoz dataset, an extension of MultiWOZ that provides emotion labels for the dialogues. MultiWOZ was partitioned initially for another purpose, resulting in a distributional shift when considering the new purpose of emotion recognition. The emotion tags in EmoWoz are highly imbalanced and unevenly distributed across the partitions, which causes sub-optimal performance and poor comparison of models. We propose a stratified sampling scheme based on emotion tags to address this issue, improve the dataset's distribution, and reduce dataset shift. We also introduce a special technique to handle conversation (sequential) data with many emotional tags. Using our proposed sampling method, models built upon EmoWoz can perform better, making it a more reliable resource for training conversational agents with emotional intelligence. We recommend that future researchers use this new partitioning to ensure consistent and accurate performance evaluations.
Foreign Direct Investment and Backward Spillovers in the Western Balkans The Context, Opportunities and Barriers to the Development of Regional Supply Chains

This article investigates how regional supply chains support the Western Balkans’ economic growth. It first identifies the role of the cefta free trade agreement in expanding the size of the local market and opening up regional trading opportunities. It recounts how the larger market and specific industrial policies have attracted foreign direct investment (fdi) to the region in recent years. It analyses how these two factors have combined to generate export-led growth in the region and have brought about substantial structural changes within these economies. The article argues that to take continued advantage of the success in trade liberalisation and fdi attraction, policymakers should pay special attention to promoting backward spillovers by promoting linkages between local small and middle sized enterprise (sme) supplier firms and the newly arrived multi national corporations embedded into global value chains. Policies should be adopted which build the capacity of local sme suppliers within regional supply chains, both in terms of labour force skills and technological © Besnik Krasniqi et al., 2022 | doi:10.30965/18763332-46010001 This is an open access article distributed under the terms of the CC BY 4.0 license. Southeastern Europe 46 (2022) 1–22 Downloaded from Schoeningh.de07/01/2023 03:10:26AM via free access
Confirmed Malaria Cases in Children under Five Years: The Influence of Suspected Cases, Tested Cases, and Climatic Conditions

Tropical and potentially fatal malaria is brought on by the parasite Plasmodium spp which spreads through infected female anopheles mosquitoes within the human populations. In Ghana, malaria is endemic and perennial, with distinct seasonal fluctuations in the northern part. Children aged below five years are among the population most vulnerable to malaria in Ghana. This study’s goal is to establish how suspected malaria cases, tested malaria cases, and climatic conditions impact confirmed malaria cases in children under five years in the Sunyani Municipality, Bono Region, Ghana. The dependent variable, monthly number of confirmed cases of malaria in children under five years, was modelled with the independent variables, monthly number of tested cases of malaria in children under five years, mean monthly relative humidity, mean monthly rainfall, and mean monthly temperature, in the Sunyani Municipality. We employed multiple linear regression after data transformation, exploratory data analysis, and correlation analysis. Results show that tested malaria cases and climatic factors significantly influence confirmed malaria cases in children under 5 years. About 41.8% of variations in confirmed malaria cases among children under 5 years is attributed to climatic factors and the number of tested cases. Moreover, results show that increase in tested cases and rainfall leads to more confirmed malaria cases among children under 5 years, while increase in temperature reduces malaria infections. To reduce the incidence of malaria in children under five years, the government and its stakeholders should encourage parent to let their children sleep in treated mosquito nets, distil stagnant waters during raining seasons, spray bushes with antimosquito insecticides, and destroy all breeding grounds of mosquitoes at all times. We proposed that all malaria cases should be laboratory tested and properly confirmed.
Effects of set-aside management on certain elements of soil biota and early stage organic matter decomposition in a High Nature Value Area, Hungary

Agricultural intensification is one of the greatest threats to soil biota and function. In contrast, set-aside still remains a management practice in certain agri-environmental schemes. In Hungary, the establishment of sown set-aside fields is a requirement of agri-environmental schemes in High Nature Value Areas. We tested the effects of set-aside management on soil biota (bacteria, microarthropods, woodlice and millipedes), soil properties and organic matter decomposition after an initial establishment period of two years. Cereal – set-aside field pairs, semi-natural grasslands and cereal fields were sampled in the Heves Plain High Nature Value Area in Eastern Hungary, in May 2014. Topsoil samples were taken from each site for physical, chemical, microbial analyses and for extraction of soil microarthropods. Macrodecomposers were sampled by pitfall traps for two weeks. The biological quality of soil was estimated by the integrated QBS index (‘‘Qualità Biologica del Suolo’’, meaning ‘‘Biological Quality of Soil’’) based on diversity of soil microarthropods. To follow early stage organic matter decomposition, we used tea bags filled with a site-independent, universal plant material (Aspalathus linearis, average mass 1.26 ± 0.03 g). Tea bags were retrieved after 1 month to estimate the rate of mass loss. We found significant differences between habitat types regarding several soil physical and chemical parameters (soil pH, K and Na content). The study showed positive effects of set-aside management on soil biodiversity, especially for Nature Conservation 29: 1–26 (2018) doi: 10.3897/natureconservation.29. 24856 http://natureconservation.pensoft. net Copyright Zsolt Tóth et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. RESEARCH ARTICLE Launched to accelerate biodiversity conservation A peer-reviewed open-access journal
On Equivalences between Weight and Function-Space Langevin Dynamics

Approximate inference for overparameterized Bayesian models appears challenging, due to the complex structure of the posterior. To address this issue, a recent line of work has investigated the possibility of directly conducting approximate inference in “function space”, the space of prediction functions. This note provides an alternative perspective to this problem, by showing that for many models – including a simplified neural network model – Langevin dynamics in the over-parameterized “weight space” induces equivalent function-space trajectories to certain Langevin dynamics procedures in function space. Thus, the former can already be viewed as a function-space inference algorithm, with its convergence unaffected by overparameterization. We provide simulations on Bayesian neural network models, and discuss the implication of the results.
COVID-19 Booster Dose Coverage and Hesitancy among Older Adults in an Urban Slum and Resettlement Colony in Delhi, India

Background: The high prevalence of vaccine booster hesitancy, with the concomitant waning of humoral vaccine or hybrid immunity, and the emergence of SARS-CoV-2 variants of concern can accentuate COVID-19 morbidity and mortality. The study objective was to ascertain the COVID-19 vaccination coverage, including the administration of precaution (booster) dose vaccination, among the older population in an urban slum and resettlement colony population in Delhi, India. Methods: We conducted a cross-sectional survey in an urban resettlement colony, slum, and village cluster in the Northeast district of Delhi among residents aged ≥50 years. Results: A total of 2217 adults (58.28%) had obtained a COVID-19 booster (precaution) dose vaccine, 1404 (36.91%) had received two doses of a COVID-19 vaccine without booster dose, 121 (3.18%) were unvaccinated, while 62 (1.63%) participants received a single dose. Based on adjusted analysis, older adults (>65 years), higher education, and higher per-capita income were statistically significant predictors of booster dose vaccination. Conclusions: More than four in ten adults in an urban slum and resettlement colony in Delhi lacked COVID-19 booster dose vaccination despite high rates of double-dose vaccination (~95%). Public health programming should provide an enhanced focus on reducing complacency with renewed prioritization for improving ease of access to COVID-19 vaccination services, particularly in underserved areas.
Co-Administration of Resolvin D1 and Peripheral Nerve-Derived Stem Cell Spheroids as a Therapeutic Strategy in a Rat Model of Spinal Cord Injury

Spinal cord injury (SCI), primarily caused by trauma, leads to permanent and lasting loss of motor, sensory, and autonomic functions. Current therapeutic strategies are focused on mitigating secondary injury, a crucial aspect of SCI pathophysiology. Among these strategies, stem cell therapy has shown considerable therapeutic potential. This study builds on our previous work, which demonstrated the functional recovery and neuronal regeneration capabilities of peripheral nerve-derived stem cell (PNSC) spheroids, which are akin to neural crest stem cells, in SCI models. However, the limited anti-inflammatory capacity of PNSC spheroids necessitates a combined therapeutic approach. As a result, we investigated the potential of co-administering resolvin D1 (RvD1), known for its anti-inflammatory and neuroprotective properties, with PNSC spheroids. In vitro analysis confirmed RvD1’s anti-inflammatory activity and its inhibitory effect on pro-inflammatory cytokines. In vivo studies involving a rat SCI model demonstrated that combined therapy of RvD1 and PNSC spheroids outperformed monotherapies, exhibiting enhanced neuronal regeneration and anti-inflammatory effects as validated through behavior tests, quantitative reverse transcription polymerase chain reaction, and immunohistochemistry. Thus, our findings suggest that the combined application of RvD1 and PNSC spheroids may represent a novel therapeutic approach for SCI management.