Miracle-dz/UniFAR-FTUs huggingface dataset:
Metaproteomic Comparison of Cryoconite Communities from Caucasian and Novaya Zemlya Glaciers

Anthropogenic pollution strongly affects glacial microbiological communities and promotes glacial melting. In the early stages of glacial melting formation of small cylindrical holes (cryoconite) occurs. While the microbiome of cryoconite is well described, the effect of anthropogenic pollution on cryoconite microbiological communities still has not been fully understood. Thus, we performed an unbiased functional comparison of the cryoconite communities from the highly polluted Caucasian glaciers and from less polluted glaciers in Novaya Zemlya. For this purpose, we used the shotgun metaproteomics approach which has not been used for cryoconite microbiome analysis previously. We identified 475 protein groups, a third of which were found in both glaciers. Cryoconites in both glaciers have similar microbiological communities with Cyanobacteria as dominant phyla. Nevertheless, we found a slight shift from the dominance of phototrophic Cyanobacteria in Novaya Zemlya to heterotrophic bacteria in the Caucasus. We assume that it might be caused by anthropogenic pollution, but other factors such as differences in seasonal dynamics of microbiological communities should be tested in the future.
Managerial Behavior, Environmental Dynamics and Organizational Performance

The performance of organizational reflects the result of the implementation of various strategies adopted by the organization. Different organizations use varying measures of performance. A recent study suggests that managerial practices are strongly connected with firm or organizational performance. A previous study discovered significant disparities in management practices among organizational and nations, and that these practices were closely linked to organizational innovation and other performance indicators including profitability and survival rates. From that, this study aims to propose a model based on the combination of managerial leadership, managerial competence, and managerial ties toward organizational performance. Also, this study highlights the role of environmental dynamics as a moderating variable. Thus, disparities in management practices were discovered to be bigger within nations than across countries, showing that some organizational and industrial elements are at least as important as the overall business environment in shaping management performance. This is due to the organization's significant contribution to a country's economic development.
Nature and Extent of International Diversification: Empirical Evidence from India

The paper aims to measure the extent of international diversification achieved by Indian companies in the recent time period. The study also investigates the nature of international diversification of companies during their transition beyond national boundaries. This evaluation of the firm’s nature and extent of internationalization is further extended to cover the period of COVID-19 as well. The Jacquemin and Berry Entropy Approach (1979) is applied to operationalize the firm’s international diversification. It facilitates the measurement of both inter-region and intra-region diversification. World Bank Geographical Region Classification Framework (2018) has been used to facilitate the applicability of the approach applied. Results indicate that Indian companies were inclined to grow beyond their home territories. However, the extent of international diversification is low as ‘Internationally Low Diversification (ILD)’ reveals to be the most popular strategy amongst Indian companies. Nature depicts a preference for relatedness than unrelatedness for overseas expansion as firms prefer intra-region expansion as compared to moving inter-region. Stagnation and halt are witnessed in the global expansion of companies in the period of the pandemic. The present study is novel as it comprehensively evaluates the international growth strategies preferred by Indian companies in the pre-pandemic and the pandemic period.
Experimental determination of ESD latent phenomena in CMOS integrated circuits

A series of measurements were performed on two types of commercially available and custom-made CMOS integrated circuits to investigate the latent mode of failure due to ESD. The current injection test method was used for both polarities of discharge. Test parameters studied included threshold failure, constant amplitude multiple stress, step stress, and the stress hardening effect. Statistical analysis of the results demonstrate the presence of latent failure in CMOS integrated circuits due to ESD. The work is used to further expand a charge injection model for latent failures. >
Spatio-temporal variability and controlling factors for postglacial erosion dynamics in the Dora Baltea catchment (western Italian Alps)

Abstract. Disentangling the influence of bedrock erodibility from the respective roles of climate, topography and tectonic forcing on catchment denudation is often challenging in mountainous landscapes due to the diversity of geomorphic processes in action and of spatial/temporal scales involved. The Dora Baltea catchment (western Italian Alps) appears the ideal setting for such investigation, since its large drainage system, extending from the Mont Blanc Massif to the Po Plain, cuts across different major litho-tectonic units of the western Alps, whereas this region has experienced homogeneous climatic conditions and glacial history throughout the Quaternary. We acquired new 10Be-derived catchment-wide denudation rates from 18 river-sand samples collected both along the main Dora Baltea river and at the outlet of its main tributaries. The inferred denudation rate results vary between 0.2 and 0.9 mm/yr, consistent with values obtained across the European Alps by previous studies. Spatial variability in denudation rates was statistically compared with topographic, environmental and geologic metrics. 10Be-derived denudation records do not correlate with the distribution of modern precipitation and rock geodetic uplift. We find, rather, that catchment topography, in turn conditioned by bedrock erodibility (litho-tectonic origin) and glacial overprint, has the main influence on denudation rates. We calculated the highest denudation rate for the Mont Blanc Massif, whose granitoid rocks and long-term tectonic uplift support steep slopes and high relief and thus favour intense glacial/periglacial processes and recurring rock fall events. Finally, our results, in agreement with modern sediment budgets, demonstrate that the high sediment input from the Mont Blanc catchment dominates the Dora Baltea sediment flux, explaining the constant low 10Be concentrations measured along the Dora Baltea course even downstream the multiple junctions with tributary catchments.
Comparison of the effects of articaine and bupivacaine in impacted mandibular third molar tooth surgery: a randomized, controlled trial

Background The aim of this randomized, triple-blind trial was to determine the anesthetic, analgesic, and hemodynamic effects of articaine and bupivacaine in the extraction of impacted mandibular third molar teeth. Methods Twenty-six patients who underwent removal of bilaterally symmetric mandibular third molars were randomly assigned to articaine and bupivacaine groups in a split-mouth design. The onset of anesthetic action, intraoperative comfort, total amount of solution used, duration of postoperative anesthesia and analgesia, rescue analgesic use, postoperative pain, intraoperative bleeding, and hemodynamic parameters were evaluated. Results In the articaine group, the onset of anesthetic activity was faster, intraoperative comfort was greater, and effective anesthesia required less local anesthetic solution. The bupivacaine group showed a significantly longer duration of postoperative anesthesia and analgesia, in addition to lower visual analog scale values at 6 and 48 hours postoperatively. There were no significant differences between the two solutions regarding rescue analgesic medication use, intraoperative bleeding, or hemodynamics. Conclusion Articaine showed greater clinical efficacy than bupivacaine in intraoperative anesthesia, achieving faster onset of anesthetic action and greater patient comfort while also requiring less reinforcement during surgery. However, bupivacaine was superior in terms of postoperative anesthesia, reducing postoperative pain due to its residual anesthetic and analgesic effects. Both anesthetic solutions led to similar hemodynamics at low doses in mandibular third molar surgery.
Combinations of Calcitriol with Anticancer Treatments for Breast Cancer: An Update

Preclinical, clinical, and epidemiological studies indicate that vitamin D3 (VD) deficiency is a risk factor for the development of breast cancer. Underlying mechanisms include the ability of calcitriol to induce cell differentiation, inhibit oncogenes expression, and modify different signaling pathways involved in the control of cell proliferation. In addition, calcitriol combined with different kinds of antineoplastic drugs has been demonstrated to enhance their beneficial effects in an additive or synergistic fashion. However, a recognized adjuvant regimen based on calcitriol for treating patients with breast cancer has not yet been fully established. Accordingly, in the present work, we review and discuss the preclinical and clinical studies about the combination of calcitriol with different oncological drugs, aiming to emphasize its main therapeutic benefits and opportunities for the treatment of this pathology.
Proportional-Fair Resource Allocation for User-Centric Networks

Considering the computational complexity and fronthaul capacity requirements of network-wide centralized optimization for Cell-free (CF) massive multiple input multiple output (MIMO) networks, we focus on user-centric (UC) networks wherein each user is served by a subset of access points (APs) rather than all the APs. We study a proportional-fair resource allocation (RA) problem, including slot resource allocation and precoding design in UC networks over consecutive time-slots. We formulate the proportional-fair (PF) resource allocation problem as a series of weighted sum-rate maximization problems and develop a two-stage heuristic RA scheme to solve the problem. The scheme adopts a user grouping process to decompose resource allocation problem into intra-group orthogonal resource allocation sub-problems. A modularity-based user grouping algorithm upon a constructed weighted digraph is proposed. Then, relying on the grouping results, a parallel distributed PFRA algorithm consisting of user selection process and a Signal to Leakage plus Noise Ratio (SLNR)-based precoding design is proposed to fulfil intra-group resource allocation. Rather than global channel state information (CSI) collected from the whole network, local CSI obtained cooperatively within each AP subset is utilized in the proposed resource allocation scheme. Numerical results confirm that the proposed RA scheme outperforms in throughput while maintaining comparable fairness among users.
Analytical Modeling of Phase 2 Steel Structure

A full‐size, six‐story, two‐bay steel structure with eccentric bracing was tested by a pseudodynamic method at the Building Research Institute, Tsukuba, Japan, during January—March 1984. The S21W 1952 Taft accelerogram was used in the elastic and inelastic tests with peak accelerations scaled to 65 and 500 gal, respectively. The structure represents phase 2 of the steel program under the U.S.‐Japan Cooperative Earthquake Research Program. The paper presents results from the pretest and refined posttest analyses. Comparisons are made with the measured global response of the structure in the elastic and inelastic level tests. The agreement between results from the refined posttest analyses and those from the tests is excellent. The analytical modeling of the structural elements is presented. The influence of various parameters upon the response is also discussed.
Case Study of High-Throughput Drug Screening and Remote Data Collection for SARS-CoV-2 Main Protease by Using Serial Femtosecond X-ray Crystallography

Since early 2020, COVID-19 has grown to affect the lives of billions globally. A worldwide investigation has been ongoing for characterizing the virus and also for finding an effective drug and developing vaccines. As time has been of the essence, a crucial part of this research has been drug repurposing; therefore, confirmation of in-silico drug screening studies has been carried out for this purpose. Here we demonstrated the possibility of screening a variety of drugs efficiently by leveraging a high data collection rate of 120 images/second with the new low-noise, high dynamic range ePix10k2M Pixel Array Detector installed at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Linac Coherent Light Source (LCLS). The X-ray Free-Electron Laser (XFEL) is used for remote high-throughput data collection for drug repurposing of the main protease (Mpro) of SARS-CoV-2 at ambient temperature with mitigated X-ray radiation damage. We obtained multiple structures soaked with 9 drug candidate molecules in two crystal forms. Although our drug binding attempts failed, we successfully established a high-throughput Serial Femtosecond X-ray crystallographic (SFX) data collection protocol.
Optimum cut-off grade’s calculation in open pit mines with regard to reducing the undesirable environmental impacts

Cut-off grade – a criterion used to discriminate ore from waste – has direct impact on mineable reserves and average grade of the materials that must be processed. The most comprehensive method for determination of optimum cut-off grades in metal deposits with the goal of maximising the net present value is provided by Lane’s algorithm. Lane’s algorithm includes income and the production costs of the final product, mining, processing and refinery capacities and grade distribution of the ore deposit, but he did not consider the reclamation costs and incomes. This study provides a model for determination of cut-off grades in open-pit mines. In this model, in addition to costs associated with management and reclamation of waste dumps, tailing dam and pits, possible incomes from reclamation are also considered. Developed model has been verified by data gathered from Gol-Gohar iron mine of Iran and results indicated that there is some important improvement in mine project goal.
Comparison of TIMS-PASEF quantitative proteomics data-analysis workflows using FragPipe, DIA-NN, and Spectronaut from a user’s perspective

Data-independent acquisition (DIA) methods have gained great popularity in bottom-up quantitative proteomics, as they overcome the irreproducibility and under-sampling limitations of data-dependent acquisition (DDA). diaPASEF, recently developed for the timsTOF Pro mass spectrometers, has brought improvements to DIA, providing additional ion separation (in the ion mobility dimension) and increasing sensitivity. Several studies have benchmarked different workflows for DIA quantitative proteomics, but mostly using instruments from Sciex and Thermo, and therefore, the results are not extrapolable to diaPASEF data. In this work, using a real-life sample set like the one that can be found in any proteomics experiment, we compared the results of analyzing PASEF data with different combinations of library-based and library-free analysis, combining the tools of the FragPipe suite, DIA-NN and including MS1-level LFQ with DDA-PASEF data, and also comparing with the workflows possible in Spectronaut. We verified that library-independent workflows, not so efficient not so long ago, have greatly improved in the recent versions of the software tools, and now perform as well or even better than librarybased ones. We report here information so that the user who is going to conduct a relative quantitative proteomics study using a timsTOF Pro mass spectrometer can make an informed decision on how to acquire (diaPASEF for DIA analysis, or DDA-PASEF for MS1-level LFQ) the samples, and what can be expected depending on the data analysis tool used, among the different alternatives offered by the recently optimized tools for TIMS-PASEF data analysis.
ORDER: Open World Object Detection on Road Scenes

Object detection is a key component in autonomous navigation systems that enables localization and classiﬁcation of the objects in a road scene. Existing object detection methods are trained and inferred on a ﬁxed number of known classes present in road scenes. However, in real-world or open-world road scenes, while inference, we come across unknown objects that the detection model hasn’t seen while training. Hence, we propose Open World Object Detection on Road Scenes (ORDER) to address the aforementioned problem for road scenes. Firstly, we introduce Feature-Mix to improve the unknown object detection capabilities of an object detector. Feature-Mix widens the gap between known and unknown classes in latent feature space that helps improve the unknown object detection. Next, we identify that the road scene dataset compared to generic object dataset contains a signiﬁcant proportion of small objects and has higher intra-class bounding box scale variations, making it challenging to detect the known and unknown objects. We propose a novel loss: Focal regression loss that collectively addresses the problem of small object detection and intra-class bounding box by penalizing more the small bounding boxes and dynamically changing the loss according to object size. Further, the detection of small objects is improved by curriculum learning. Finally, we present an extensive evaluation on two road scene datasets: BDD and IDD. Our experimental evaluations on BDD and IDD shows consistent improvement over the current state-of-the-art
Adaptive Cross-Attention-Driven Spatial–Spectral Graph Convolutional Network for Hyperspectral Image Classification

Recently, graph convolutional networks (GCNs) have been developed to explore the spatial relationship between pixels, achieving better classification performance of hyperspectral images (HSIs). However, these methods fail to sufficiently leverage the relationship between spectral bands in HSI data. As such, we propose an adaptive cross-attention-driven spatial–spectral graph convolutional network (ACSS-GCN), which is composed of a spatial GCN (Sa-GCN) subnetwork, a spectral GCN (Se-GCN) subnetwork, and a graph cross-attention fusion module (GCAFM). Specifically, Sa-GCN and Se-GCN are proposed to extract the spatial and spectral features by modeling the correlations between spatial pixels and between spectral bands, respectively. Then, by integrating attention mechanism into information aggregation of the graph, the GCAFM, including three parts, i.e., the spatial graph attention block, the spectral graph attention block, and the fusion block, is designed to fuse the spatial and spectral features, and suppress noise interference in Sa-GCN and Se-GCN. Moreover, the idea of the adaptive graph is introduced to explore an optimal graph through backpropagation during the training process. Experiments on two HSI datasets show that the proposed method achieves better performance than other classification methods.
Reactivation of hedonic but not sensory representations in human emotional learning

Learning which stimuli in our environment co-occur with painful or pleasurable events is critical for survival. Previous research has established the basic neural and behavioural mechanisms of aversive and appetitive conditioning; however, it is unclear what precisely is learned. Here we examined what aspects of the unconditioned stimulus (US) – sensory and hedonic – are transferred to the conditioned stimulus (CS). To decode the content of brain activation patterns elicited during appetitive (soft touch) and aversive (painful touch) conditioning of faces, a novel variation of representational similarity analysis (RSA) based on theoretically driven representational patterns of interest (POIs) was applied to fMRI data. Once face associations were learned through conditioning, globally the CS reactivated US representational patterns showing conditioning-dependent reactivation. More specifically, in higher order brain regions, the CS only reactivated hedonic but not sensory aspects of the US – suggesting that affective conditioning primarily carries forward the valence of the experience rather than its sensory origins.
The refractive index sensor of the SMF covered by nanodiamond layer

* Corresponding Author Email: m.nadafan@sru.ac. ir How to cite this article Nadafan M. , Zamir Anvari J., Ahmadian A. , Reyhani Clor Z. The refractive index sensor of the SMF covered by nanodiamond layer. Int. J. Nano Dimens. , 2022; 13(1): 96-104. Abstract This study evaluated the light transmission characteristics of a single modular fiber with a cylindrical microchannel using the FDTD method. To this end, various microchannel diameters (4-11μm) were explored. The SMF included a silica core (n=1.4) coated by a nanodiamond layer with a refractive index of 2.42. The impact of Fabry-Perot resonance was evidently detected in transmission features. At constant λ, the light transmission variations depended on the refractive index of the microchannel. A significant change was observed in the upon altering the microchannel refractive index. Based on the results, a microchannel-based SMF with different diameters can be employed for refractive index sensing. In the cases where the diameter of the microchannel largely differs from that of the core (8μm), the transmission variations were negligible. The numerical results are in good agreement with those reported in the microhole or microchannel experiment. The highest and lowest transmissions were recorded for the microchannel at diameters of 4 and 11μm, respectively. Comparing related experimental and numerical results show proper control of the microchannel diameter can enhance light transmission through the core-microchannel. The sensitivity of the refractive index to the microchannel diameter is a promising feature that can be exploited for developing various fiber optical devices.
Boardroom Racial (In)Equality and Stock Returns: Evidence from the Black Lives Matter Protests

We study a cross-section of stock price reactions to the Black Lives Matter (BLM) protests that followed the killing of George Floyd on May 25, 2020. We find that companies with higher representation of black directors on the corporate board are associated with higher stock returns during the mass BLM protests. This exogenous shock (BLM protests) provides an opportunity to evaluate the relationship between boardroom racial diversity and firm value. Using a sample of S&P 500 index companies, we find that before the killing of George Floyd black directors held on average 8.2% of the board seats, with each black director holding on average 1.34 board seats, which is significantly higher than for directors of other ethnic origins. Within one year after the mass BLM protests, the proportion of board seats held by black directors increased to 9.6%, and 31% of the newly appointed directors were black. We find that companies typically add new diverse directors by increasing the board size. Additionally, we show evidence that boards are paying more attention to racial diversity issues in the aftermath of the BLM protests, and only a low correlation exists between talking about racial diversity in proxy statements and actual racial diversity in the boardroom.