Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Designer Benzodiazepines: Comprehensive Review of Evolving Clinical and Adverse Effects

As tranquilizers, benzodiazepines have a wide range of clinical uses. Recently, there has been a significant rise in the number of novel psychoactive substances, including designer benzodiazepines. Flubromazolam(8-bromo-6-(2-fluorophenyl)-1-methyl-4H-[1,2,4]triazolo[4,3-a][1,4]benzodiazeZpine) is a triazolo-analogue of flubromazepam. The most common effects noted by recreational users include heavy hypnosis and sedation, long-lasting amnesia, and rapid development of tolerance. Other effects included anxiolysis, muscle-relaxing effects, euphoria, loss of control, and severe withdrawals. Clonazolam, or 6-(2-chlorophenyl)-1-methyl-8-nitro-4H-[1,2,4]triazolo[4,3-α]-[1,4]-benzodiazepine, is a triazolo-analog of clonazepam. It is reported to be over twice as potent as alprazolam. Deschloroetizolam (2-Ethyl-9-methyl-4-phenyl-6H-thieno[3,2-f][1,2,4]triazolo[4,3-a][1,4]diazepine) is part of the thienodiazepine drug class, which, like benzodiazepines, stimulates GABA-A receptors. Meclonazepam ((3S)-5-(2-chlorophenyl)-3-methyl-7-nitro-1,3-dihydro-1,4-benzodiazepin-2-one) is a designer benzodiazepine with additional anti-parasitic effects. Although it has proven to be an efficacious therapy for schistosomiasis, its sedative side effects have prevented it from being marketed as a therapeutic agent. The use of DBZs has been a subject of multiple recent clinical studies, likely related to increasing presence and availability on the internet drug market and lack of regulation. Many studies have aimed to identify the prevalence of DBZs and their effects on those using them. This review discussed these designer benzodiazepines and the dangers and adverse effects that the clinician should know.
Fuzzy Sparse Deviation Regularized Robust Principal Component Analysis

Robust principal component analysis (RPCA) is a technique that aims to make principal component analysis (PCA) robust to noise samples. The current modeling approaches of RPCA were proposed by analyzing the prior distribution of the reconstruction error terms. However, these methods ignore the influence of samples with large reconstruction errors, as well as the valid information of these samples in principal component space, which will degrade the ability of PCA to extract the principal component of data. In order to solve this problem, Fuzzy sparse deviation regularized robust principal component Analysis (FSD-PCA) is proposed in this paper. First, FSD-PCA learns the principal components by minimizing the square of $\ell _{2}$ -norm-based reconstruction error. Then, FSD-PCA introduces sparse deviation on reconstruction error term to relax the samples with large bias, thus FSD-PCA can process noise and principal components of samples separately as well as improve the ability of FSD-PCA for retaining the principal component information. Finally, FSD-PCA estimates the prior probability of each sample by fuzzy weighting based on the relaxed reconstruction error, which can improve the robustness of the model. The experimental results indicate that the proposed model performs excellent robustness against different types of noise than the state-of-art algorithms, and the sparse deviation term enables FSD-PCA to process noise information and principal component information separately, so FSD-PCA can filter the noise information of an image and restore the corrupted image.
Using Machine Learning for Predicting the Effect of Mutations in the Initiation Codon

The effect of mutations has been traditionally predicted by studying what may happen due to the substitution of one amino acid for another one. This approach may be effective for mutations with impact in the function of the protein, but ineffective for mutations in the translation initiation codon. Such mutation might avoid the generation of the protein. Consequently, specific methods for predicting the effect of mutations in the translation initiation codon are needed. We propose a method for predicting the effect of mutations in the canonical translation initiation codon based on a biological model that considers specific features of such mutations, like the distance to a potential alternative initiation codon. Our predictor has been developed using tree-based machine learning algorithms and data extracted from Ensembl. Our final model is able to detect whether a mutation in the canonical initiation codon is deleterious or benign with a precision of 44.28% and an accuracy of 98.32%, which improves the results of state of the art tools such as PolyPhen, SIFT, or CADD for this type of mutation.
Response to Letter by Hsia et al, Titled “Advanced Imaging for Mild Stroke Patients–Selection for Acute Interventions”

We appreciate the interest by Dr. Hsia and colleagues in our article discussing potential advanced imaging-based selection par-adigm for patients presenting with mild strokes. 1 The management and selection for reperfusion therapies is challenging in this cohort because of signi ﬁ cant heterogeneity in presentation, natu-ral history supporting higher likelihood of a good clinical out-come, and potential risks associated with reperfusion therapies. In our study, 2 the EXTEND-IA trials contributed 40 patients with NIHSS 0 – 5. The focus of our research was to evaluate mild strokes presenting with large vessel occlusions that are potentially amenable to endovascular therapy. While the overall incidence of patients presenting with mild strokes is high (~50% of all strokes), 3 patients with mild strokes and large vessel occlusion (LVO) represent a much smaller population (~5% of all stro-kes). 4, 5 This population differs from patients with mild stroke without LVO in their higher risk of neurological deterioration, resulting in poorer outcomes. The procedural risks are also higher, 2, 6 – 8 thus the heightened need for patient selection. Most endovascular thrombectomy (EVT) centers are equipped with advanced imaging modalities, making it feasible to adapt advanced imaging-based selection paradigms for EVT in these patients. AHA/ASA guidelines recommend using DWI/FLAIR mismatch in extended time window (beyond 4.5 h) to determine eligibility for intravenous (IV) thrombolytics. 9 Australian guidelines and at both comprehensive stroke centers (CSCs) and primary stroke centers (PSCs), CT perfusion mismatch used to identify patients for IV throm-bolytic beyond 4.5 h and EVT beyond 6 h, with MR perfusion-diffusion mismatch an alternative if accessible within an acceptable timeframe. We agree
Awe as a Pathway to Mental and Physical Health

How do experiences in nature or in spiritual contemplation or in being moved by music or with psychedelics promote mental and physical health? Our proposal in this article is awe. To make this argument, we first review recent advances in the scientific study of awe, an emotion often considered ineffable and beyond measurement. Awe engages five processes—shifts in neurophysiology, a diminished focus on the self, increased prosocial relationality, greater social integration, and a heightened sense of meaning—that benefit well-being. We then apply this model to illuminate how experiences of awe that arise in nature, spirituality, music, collective movement, and psychedelics strengthen the mind and body.
The Armed Conflict and the Impact on Patients With Cancer in Ukraine: Urgent Considerations

On February 24, 2022, a war began within the Ukrainian borders. At least 3.0 million Ukrainian inhabitants have already fled the country. Critical infrastructure, including hospitals, has been damaged. Children with cancer were urgently transported to foreign countries, in an effort to minimize interruption of their life-saving treatments. Most adults did not have that option. War breeds cancer—delaying diagnosis, preventing treatment, and increasing risk. We project that a modest delay in care of only 4 months for five prevalent types of cancer will lead to an excess of over 3,600 cancer deaths in the subsequent years. It is critical that we establish plans to mitigate that risk as soon as possible.
The Antarctic ozone hole and the pattern effect on climate sensitivity

Significance We provide a perspective on recent scientific literature that argues the reduction in climate sensitivity identified with relative cooling in the eastern tropical Pacific Ocean could be caused by the onset of the Antarctic ozone hole starting in about 1980. If this is true, the pattern effect could persist as long as the ozone hole, nearly 60 y. This would continue the reduction in warming associated with the pattern effect on climate sensitivity. In addition, increased probability of La Niña events would imply an increased chance of drought in the American Southwest and other impacts of cooling in the eastern tropical Pacific.
Questionnaires of interoception do not assess the same construct

There are a number of questionnaires assessing the self-reported trait-like aspect of interoception, also called interoceptive sensibility (ISb). Based on the varying purposes of their development and characteristics, however, it is not likely that they assess exactly the same construct. In a community sample of 265 adults, we examined this assumption for three commonly used questionnaires of ISb, namely the Body Awareness subscale of the Body Perception Questionnaire (BPQ-BA), the Body Awareness Questionnaire (BAQ), and the eight subscales of Multidimensional Assessment of Interoceptive Awareness (MAIA). We investigated their associations, and their relation to positive and negative affect and somatosensory amplification. According to the results of correlation analysis, BPQ-BA, BAQ and MAIA were partly unrelated to each other, partly showed weak to moderate positive associations. Also, differences with respect to their association with positive and negative affect were found. These findings suggest that the investigated questionnaires cannot be used interchangeably to assess the subjective aspect of interoception, and the term ISb is not appropriately defined.
Effects of chemical warfare agent decontaminants on trace survival: Impact on fingermarks deposited on glass

Following a chemical incident involving chemical warfare agents or more broadly, chemical weapons, there are two possible approaches in dealing with the traditional forensic analysis of contaminated exhibits. The first is to analyze the contaminated items under safe conditions (i.e. in laboratories dedicated to the handling of such substances), while the second relies on item decontamination prior to processing them in traditional forensic laboratories. One of the main limitations of the latter is the possible degradation or destruction of traces caused by the decontamination process. Hence, it is crucial to have as much information as possible on the impact of different decontamination agents and procedures on traces. This research presents experimental results on the recovery of fingermarks on glass after the application of decontaminants typically used in case of chemical incidents. The impact of 11 decontaminants on fingermarks deposited on glass and on the subsequent enhancement with cyanoacrylate and Small Particle Reagent (SPR) was evaluated (by visual examination) by four evaluators. The results of the study demonstrated that the persistence of fingermarks on glass is highly dependent on the type of decontaminant used. Decontamination agents based on the principle of nucleophilic substitution to neutralize toxic chemicals allowed good subsequent development of fingermarks with SPR. Powdered decontaminants did not show any indication of alteration of fingermarks, whereas decontamination with oxidants leads to variable results.
Explaining Putin’s impunity: public sector corruption and political trust in Russia

ABSTRACT While corruption of different types has been shown to lower popular political trust in democratic regimes, evidence from non-democracies remains inconsistent. In some post-Soviet countries, for instance, widespread bribery and nepotism in the government co-exist with enduring popularity of top political leadership. Drawing on an unusually nuanced dataset from Russia (N = 2,350), we show that, in general, encounters with corruption in the public sector are associated with citizens’ lower trust of their government. At the same time, we theorize two caveats that attenuate this relationship, contributing to inconsistent findings in previous studies. First, we find that the negative association between corruption and political trust is significantly weaker when such corruption is beneficial to ordinary people. Second, citizens tend to “penalize” local rather than central government officials, which, we argue, is a result of top leaders’ ability to manipulate public discourse around corruption.
Lymphoedema conditions disrupt endothelial barrier function in vitro

Lymphatic vessel contractions generate net antegrade pulsatile lymph flow. By contrast, impaired lymphatic vessels are often associated with lymphoedema and altered lymph flow. The effect of lymphoedema on the lymph flow field and endothelium is not completely known. Here, we characterized the lymphatic flow field of a platelet-specific receptor C-type lectin-like receptor 2 (CLEC2) deficient lymphoedema mouse model. In regions of lymphoedema, collecting vessels were significantly distended, vessel contractility was greatly diminished and pulsatile lymph flow was replaced by quasi-steady flow. In vitro exposure of human dermal lymphatic endothelial cells (LECs) to lymphoedema-like quasi-steady flow conditions increased intercellular gap formation and permeability in comparison to normal pulsatile lymph flow. In the absence of flow, LECs exposed to steady pressure (SP) increased intercellular gap formation in contrast with pulsatile pressure (PP). The absence of pulsatility in steady fluid flow and SP conditions without flow-induced upregulation of myosin light chain (MLCs) regulatory subunits 9 and 12B mRNA expression and phosphorylation of MLCs, in contrast with pulsatile flow and PP without flow. These studies reveal that the loss of pulsatility, which can occur with lymphoedema, causes LEC contraction and an increase in intercellular gap formation mediated by MLC phosphorylation.
Orchestrated Biosynthesis of the Secondary Metabolite Cocktails Enables the Producing Fungus to Combat Diverse Bacteria

Fungal chemical ecology is largely mediated by the metabolite(s) produced by individual biosynthetic gene clusters (BGCs) with antibiotic activities. We report a supercluster containing three BGCs that are jointly controlled by an embedded master regulator in the insect pathogen Metarhizium robertsii. ABSTRACT Fungal secondary metabolites with antibiotic activities can promote fungal adaptation to diverse environments. Besides the global regulator, individual biosynthetic gene clusters (BGCs) usually contain a pathway-specific transcription factor for the tight regulation of fungal secondary metabolism. Here, we report the chemical biology mediated by a supercluster containing three BGCs in the entomopathogenic fungus Metarhizium robertsii. These clusters are jointly controlled by an embedded transcription factor that orchestrates the collective production of four classes of chemicals: ustilaginoidin, indigotide, pseurotin, and hydroxyl-ovalicin. The ustilaginoidin BGC is implicated as a late-acquired cluster in Metarhizium to produce both the bis-naphtho-γ-pyrones and the monomeric naphtho-γ-pyrone glycosides (i.e., indigotides). We found that the biosynthesis of indigotides additionally requires the functions of paired methylglucosylation genes located outside the supercluster. The pseurotin/ovalicin BGCs are blended and mesosyntenically conserved to the intertwined pseurotin/fumagillin BGCs of Aspergillus fumigatus. However, the former have lost a few genes, including a polyketide synthase gene responsible for the production of a pentaene chain used for assembly with ovalicin to form fumagillin, as observed in A. fumigatus. The collective production of chemical cocktails by this supercluster was dispensable for fungal virulence against insects and could enable the fungus to combat different bacteria better than the metabolite(s) produced by an individual BGC could. Thus, our results unveil a novel strategy employed by fungi to manage chemical ecology against diverse bacteria. IMPORTANCE Fungal chemical ecology is largely mediated by the metabolite(s) produced by individual biosynthetic gene clusters (BGCs) with antibiotic activities. We report a supercluster containing three BGCs that are jointly controlled by an embedded master regulator in the insect pathogen Metarhizium robertsii. Four classes of chemicals, namely, ustilaginoidin, indigotide, pseurotin, and hydroxyl-ovalicin, are collectively produced by these three BGCs along with the contributions of tailoring enzyme genes located outside the supercluster. The production of these metabolites is not required for the fungal infection of insect hosts, but it benefits the fungus to combat diverse bacteria. The findings reveal and advocate a “the-more-the-better” strategy employed by fungi to manage effective adaptations to diverse environments.
Removing or Avoiding the Camera Focus Light Appearing on Glossy or Bouncing Surfaces by Light Guiding and Image Warping

Digital picture or image becomes more and more important in people's daily life, such as for administration, documentation, active communications, and learning processes. People also demand the exchange of information through digital applications and social media. Taking picture or photo of a document, book, certificate, or thing is usually done by the help of digital scanner, but not all these stuffs can be converted into digital with a scanner. In specific condition people need real image transfer and will take photo of the real view directly using their own digital camera or smartphone camera. From author experience and observations, when taking photos of a document or book or certificate or thing normally with plastic cover or glass surface or bouncing surface, we clearly got an annoying light came from the camera focus light or flash that usually creates noise and messy image. This research was conducted based on the idea to remove or avoid getting the unwanted or disturbing light while taking photos of glossy or bouncing surfaces. A procedure to get a clear and smooth image instead of noise and broken image was derived and implemented by author using light guiding and image warping. These two methods bring accurate images that are necessary for communication needs and facilitate better future works without compromising security policies and people's rights. As the research methodology, author performed literature study, observation, analysis, and implementation. The result of this research offers a good procedure and method that can help people getting clear photos or pictures of a glossy or bouncing surface, advance research to be implemented related to camera technology, and best comprehension to improve photography techniques for future developments.
REACT: a heterogeneous reconfigurable neural network accelerator with software-configurable NoCs for training and inference on wearables

On-chip training improves model accuracy on personalised user data and preserves privacy. This work proposes REACT, an AI accelerator for wearables that has heterogeneous cores supporting both training and inference. REACT's architecture is NoC-centric, with weights, features and gradients distributed across cores, accessed and computed efficiently through software-configurable NoCs. Unlike conventional dynamic NoCs, REACT's NoCs have no buffer queues, flow control or routing, as they are entirely configured by software for each neural network. REACT's online learning realises upto 75% accuracy improvement, and is upto 25× faster and 520× more energy-efficient than state-of-the-art accelerators with similar memory and computation footprint.
A defect tolerance framework for improving yield

In the latest technology nodes, there is a growing concern about yield loss due to timing failures and delay degradation resulting from manufacturing complexities. Largely, these process imperfections are fixed using empirical methods such as layout guidelines and process fixes which come late during the design cycle. In this work, we propose a framework for improving the design yield by synthesizing netlists with improved ability to withstand delay variations to reduce yield loss. We advocate a defect tolerant approach during early design stages to synthesize netlists by introducing defect-awareness to EDA synthesis, thereby generating robust netlists that can withstand delays induced by process imperfections. Toward this objective, we present a) a methodology to characterize standard library cells for delay defects to model the robustness of the cell delays, and b) a solution to drive design synthesis using the intelligence from the cell characterization to achieve design robustness to timing errors. We also introduce defect tolerance metrics to quantify the robustness of standard cells to timing variations, which we use to generate defect-aware libraries to guide defect-aware synthesis. Effectiveness of the proposed defect-aware methodology is evaluated on a set of benchmarks implemented in GF 12nm technology using static timing analysis (STA), revealing a 70--80% reduction of yield loss due to timing errors arising from manufacturing defects, with minimum impact on the area, power and no impact on performance.
DA PUF: dual-state analog PUF

Physical unclonable function (PUF) is a promising lightweight hardware security primitive that exploits process variations during chip fabrication for applications such as key generation and device authentication. Reliability of the PUF information plays a vital role and poses a major challenge for PUF design. In this paper, we propose a novel dual-state analog PUF (DA PUF) which has been successfully fabricated in 55nm process. The 40,960 bits generated by the fabricated DA PUF pass the NIST randomness test with reliability over 99.99% for working environment of -40 ~ 125° C (temperature) and 0.96 ~ 1.44V (voltage), outperforming the two state-of-the-art analog PUFs reported in JSSC 2016 and 2021.
GraphRing: an HMC-ring based graph processing framework with optimized data movement

Due to the irregular memory access and high bandwidth demanding, graph processing is usually inefficient on conventional computer architectures. The recent development of the processing-in-memory (PIM) technique such as hybrid memory cube (HMC) has provided a feasible design direction for graph processing accelerators. Although PIM provides high internal bandwidth, inter-node memory access is inevitable in large-scale graph processing, which greatly affects the performance. In this paper, we propose an HMC-based graph processing framework, GraphRing. GraphRing is a software-hardware codesign framework that optimizes inter-HMC communication. It contains a regularity- and locality-aware graph execution model and a ring-based multi-HMC architecture. The evaluation results based on 5 graph datasets and 4 graph algorithms show that GraphRing achieves on average 2.14× speedup and 3.07× inter-HMC communication energy saving, compared with GraphQ, a state-of-the-art graph processing architecture.