Miracle-dz/UniFAR-FTUs huggingface dataset:
Rates of surgical deaths and infections at district hospitals in Malawi and Zambia: a prospective multicentre cohort study

Objective This paper reports perioperative mortality and postoperative infection rates of surgical patients who underwent operations at district-level hospitals in Malawi and Zambia, and the associations of these outcomes with patient characteristics based on routinely available data. Design Prospective cohort study. Setting Eight government district hospitals in Malawi and nine mission and government district hospitals in Zambia. Outcome measures Perioperative mortality and postoperative infection were used as primary outcome measures in this study. Logistic regression and penalised maximum likelihood logistic regression were used to examine the factors correlated with surgical outcomes. Results The average perioperative mortality rates were 0.19% and 0.43% in Malawi and Zambia, respectively. Penalised maximum likelihood logistic regression showed that age (OR=1.046, 95% CI 1.016 to 1.078) and American Society of Anesthesiologists physical status score II (OR=6.658, 95% CI 2.363 to 18.762) were significantly associated with perioperative deaths. General surgery procedures were significantly more likely than obstetrical procedures to result in perioperative deaths (OR=3.821, 95% CI 1.226 to 11.908). The average rates of postoperative infections in Malawi and Zambia were 2.69% and 2.24%, respectively. Age (OR=1.010, 95% CI 1.000 to 1.020) and male sex (OR=0.407, 95% CI 0.260 to 0.637) were significantly associated with postoperative infections. Additional factors, general procedures (OR=2.319, 95% CI 1.397 to 3.850) and trauma-related procedure (OR=5.490, 95% CI 2.632 to 11.449) were significantly associated with infection rates. There was no significant correlation between surgical outcomes and cadre of lead surgeon (a non-physician clinician or doctor). Conclusion Rates of mortality and postoperative infections in this sample of district-level hospitals in Malawi and Zambia were relatively low, with poorer preoperative physical status as the main predictor of both greater postoperative infection and mortality. The study demonstrates that outcomes of major surgical cases do not depend on the cadre (type) of surgeon performing it, and outcomes can be monitored using routine data, at district level in these countries. Trial registration number ISRCTN66099597.
A new variant of the human α-lactalbumin-oleic acid complex as an anticancer agent for chronic myeloid leukemia

Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder of hematopoietic stem cells. Although there have been advancements in treatment, there is still a need to develop a biotherapeutic agent. A new variant of the human alpha-lactalbumin-oleic acid (HALOA) complex has been synthesized, which showed similarities with SNARE. The native α-LA was treated with EDTA to remove Ca2+ ions confirmed by ICP-OES and Arsenazo III to unfold and attain apo structure. The apo LA was mixed with OA in a specific ratio, leading to HALOA complex formation. The conformational state from native to complex was elucidated by circular dichroism (far; 190–260 nm and near; 260–340 nm UV-CD), which confirmed that the complex consists of a majority of turns and β-sheet structure. SDS-PAGE result showed the masking effect of OA on apo α-LA. In the lane of the complex, there was no band detected. However, 1-anilino-8-naphthalene sulfonate (ANS) dye has shown maximum fluorescence intensity with the complex because of the availability of hydrophobic patches, which was further validated by NMR spectroscopy indicating the masking effect of OA on the apo α-LA. The SNARE behavior of the complex (500 nm) has been confirmed by TEM. This new structural variant complex shows anti-tumor activity on chronic myeloid leukemia by targeting the IL-8, survivin, and induces apoptosis through DNA fragmentation, but not against normal cells. Overall, the formulated complex shows that SNARE-like behavior can be used as a promising anti-tumor agent with lower toxicity and maximum bioavailability.
Antioxidant enzymes and vascular diseases

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) play a fundamental role in regulating endothelial function and vascular tone in the physiological conditions of a vascular system. However, oxidative stress has detrimental effects on human health, and numerous studies confirmed that high ROS/RNS production contributes to the initiation and progression of cardiovascular diseases. The antioxidant defense has an essential role in the homeostatic functioning of the vascular endothelial system. Endogenous antioxidative defense includes various molecules and enzymes such as superoxide dismutase, catalase, glutathione reductase, and glutathione peroxidase. Together all these antioxidative enzymes are essential for defense against harmful ROS features. ROS are mainly generated from redox-active compounds involved in the mitochondrial respiratory chain. Thus, targeting antioxidative enzymes and mitochondria oxidative balance may be a promising approach for vascular diseases occurrence and treatment. This review summarized the most recent research on the regulation of antioxidative enzymes in vascular diseases.
Mirror Therapy Rehabilitation in Stroke: A Scoping Review of Upper Limb Recovery and Brain Activities

Background Mirror therapy (MT) has been used as a treatment for various neurological disorders. Recent application of electroencephalogram (EEG) to the MT study allows researchers to gain insight into the changes in brain activity during the therapy. Objective This scoping review is aimed at mapping existing evidence and identifying knowledge gaps about the effects of MT on upper limb recovery and its application for individuals with chronic stroke. Methods and Materials A scoping review through a systematic literature search was conducted using PubMed, CINAHL, PsycINFO, and Scopus databases. Twenty articles published between 2010 and 2020 met the inclusion criteria. The efficacy of MT on upper limb recovery and brain activity during MT were discussed according to the International Classification of Functioning, Disability and Health (ICF). Results A majority of the studies indicated positive effects of MT on upper limb recovery from the body structure/functional domain. All studies used EEG to indicate brain activation during MT. Conclusion MT is a promising intervention for improving upper limb function for individuals with chronic stroke. This review also highlights the need to incorporate EEG into the MT study to capture brain activity and understand the mechanism underlying the therapy.
FACE RECOGNITION USING HYBRID GABOR FILTER AND STACKED SPARSE AUTO ENCODERS (SSAE) WITH DEEP NEURAL NETWORK MODEL

Face recognition has been getting greater attention especially since most recognition systems are easily penetrated or copied. However, the accuracy of face recognition is very important in determining the success in identifying an individual. One of the hurdles that hampered the accuracy of face recognition is when the dataset is limited. Especially in traditional machine learning algorithms that are used for face recognition based on images requires sufficient training data to enable high levels of face recognition accuracy. Based on the afore-mentioned problem, a study was carried out to enhance face recognition technique by using hybrid Gabor Filter and deep learning Stacked Sparse Auto Encoders (SSAE). The experimental evaluation was carried out using two datasets which are Olivetti Research Laboratory OLR and Extended Yale-B databases. All face images are greyscale, and the resolution 92 × 112 for OLR database while 192×168 resolution for Extended Yale-B database. The result of the evaluation showed that the accuracy of face recognition has been improved by using proposed method and get best accuracy among all experimented State-of-the-Art methods on both of OLR and Extended Yale-B databases.
Modeling of Metal Forming and Machining Processes: by Finite Element and Soft Computing Methods (Engineering Materials and Processes) (Engineering Materials and Processes)

The physics of metal forming and metal removing is normally expressed using non-linear partial differential equations which can be solved using the finite element method (FEM). However, when the process parameters are uncertain and/or the physics of the process is not well understood, soft computing techniques can be used with FEM or alone to model the process. Using FEM, fuzzy set theory and neural networks as modeling tools; Modeling of Metal Forming and Machining Processes provides a complete treatment of metal forming and machining, and includes: an explanation of FEM and its application to the modeling of manufacturing processes; a discussion of the numerical difficulties of FEM; chapters on the application of soft computing techniques in this modeling process. The algorithms and solved examples included make Modeling of Metal Forming and Machining Processes of value to postgraduates, senior undergraduates, lecturers and researchers in these fields. R&D engineers and consultants for the ma nufacturing industry will also find it of use.
Thermo Activated Hysteresis on High Quality Graphene/h-BN Devices

We report on gate hysteresis in resistance on high quality graphene/h-BN devices. We observe a thermal activated hysteretic behavior in resistance as a function of the applied gate voltage at temperatures above 375K. In order to investigate the origin of the hysteretic phenomenon, we design heterostructures involving graphene/h-BN devices with different underlying substrates such as: SiO2/Si and graphite; where heavily doped silicon and graphite are used as a back gate electrodes, respectively. The gate hysteretic behavior of the resistance shows to be present only in devices with an h-BN/SiO2 interface and is dependent on the orientation of the applied gate electric field and sweep rate. Finally, we suggest a phenomenological model, which captures all of our findings based on charges trapped at the h-BN/SiO2. Certainly, such hysteretic behavior in graphene resistance represents a technological problem for the application of graphene devices at high temperatures, but conversely, it can open new routes for applications on digital electronics and graphene memory devices.
Revitalisation Strategies For Modern GlassFacades Of The 20th Century

Modern glass facades of the early and mid 20 century have always been synonymous with innovative and sophisticated building concepts. These building skins were often established as a feature reflecting international stylistic standards, enhancing the prestige of builders and occupants – although often independent from or even in contradiction with climatic requirements and local conditions. In particular, in Central Europe varying strategies for the revitalisation of modern glass walls, facades and windows have been developed and realised. Multi-storey and high-rise buildings from the 1950s and 1960s, such as Haus Hardenberg by Paul Schwebes (1955-56) and Europa-Centre by Helmut Hentrich and Huber Petschnigg (1965), both in Berlin, are typical facade constructions. The very diverse approaches of revitalisation of Haus Hardenberg and the Europa-Centre will serve as examples to be compared and described with regard to different planning and decision frameworks. Both buildings have passed through certain episodes of modification and revitalisation. Both are preserving their original appearance, but while the original facade construction of Haus Hardenberg has been maintained and modified, the single glass facade of the Europa-Centre has been totally changed into a double facade system. The architectural design, construction, functions and environmental qualities will be described and evaluated with regard to the original concepts and requirements. These buildings will be presented addressing their impact on the refurbishment of modern building skins in general and in relation to increasing energetic requirements. In this context newly developed steel profiles have been investigated to be used as an alternative for the revitalisation of protected facade constructions. The way in which Modern Movement buildings in other countries and continents can be adapted to climatic and socio-economic conditions will also be discussed.
A GIBBERELLIN, ABSCISIC ACID, AND DELAY OF GERMINATION 1 INTERACTION NETWORK REGULATES CRITICAL DEVELOPMENTAL TRANSITIONS IN MODEL PLANT ARABIDOPSIS THALIANA – A REVIEW

Seed germination and flowering are two critical developmental transitions in the life cycles of plants. These transitions are coordinately regulated by exogenous environmental cues and endogenous hormonal signals to match plant establishment and reproduction to the appropriate seasons. The phytohormones, abscisic acid (ABA) and gibberellins (GAs), are the key players that antagonistically regulate seed dormancy and germination; ABA positively modulates dormancy induction and maintenance, while GA stimulates germination. For the control of flowering time, GA has been shown to have a positive role in the modulation of floral transition, whereas both positive and negative roles have been recorded for ABA in this process. DELAY OF GERMINATION 1 (DOG1) delays floral transition and functions in dormancy induction and maintenance, acting in parallel with ABA and/or GA. However, DOG1 is also involved in ABA and GA antagonism through affecting hormone biosynthesis and/or signal transduction pathways. Moreover, the expression of DOG1 is directly regulated by ABA. In this review, we summarize recent developments in seed dormancy and flowering research on the model plant Arabidopsis thaliana, focusing on the crosstalk between ABA, GA, and DOG1. Finally, the open questions and remaining challenges in this field are presented.
Tentative guidelines for waste selection, process design, operation and control of upflow anaerobic sludge bed reactors

Successful application of upflow anaerobic sludge bed (UASB) technology hinges on the generation of sludge aggregating into bio-conglomerates, to facilitate retention of the sludge in the reactor. In this paper an hypothesis for formation of one type of bio-conglomerate, the biopellet, is presented. From the hypothesis, characteristics that a waste must possess to induce pelletization, and process design and operational procedures to optimize system performance, are identified.
Effect of sowing date and foliar application of salicylic acid on forage yields and quality of globe artichoke ( Cynara scolymus

In northern latitudes, productivity of forage crop s could be affected by weather conditions at sowing as well as during harvesting. Manag ement of sowing date and foliar application of growth regulators can help to avoid severe environm ental stresses during these sensitive stages and may improve forage quality. Globe artichoke ( Cynara scolymus L.) has been recently introduced as a specialty and alternative forage crop in north -western Iran. Morphological characteristics, yield and quality of forage of artichoke leaves wer e investigated in response to three (April 19, May 5 and 20) sowing dates and three acid salicylic (0, 700 and 1400 μM) rates of foliar spray under field condition. Foliar application of 700 an d 1400 μM salicylic acid solution caused to 18% and 26% increase in leaf number, respectively. Results showed that digestible dry matter (DDM), crude protein, crude fat and ash were affect ed by both sowing date and salicylic acid. The highest digestible dry matter was recorded in third sowing date with 700 μM salicylic acid application. On the other hand the maximum yield and dry m atter, crude fat and protein were observed in second sowing date. Based on these results, we estim ate that under these environmental conditions, second sowing date (May 5) along with 700 μM salicylic acid foliar application appear sufficient to obtain high yield and acceptable forg e quantity of artichoke.
БИОЛОГИЧЕСКИЕ НАУКИ GLYCOCONJUGATES IN PROGNOSTIC ANALYSIS AGAINST INFECTIONS AND PATHOGENS : THE KEYS TO APPLICATION

Lakhtin V.M. G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology, Admiral Makarov Street 10, Moscow 125212, Russia Lakhtin M.V. G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology, Admiral Makarov Street 10, Moscow 125212, Russia Melikhova A.V. G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology, Admiral Makarov Street 10, Moscow 125212, Russia Davydkin I.Yu. G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology, Admiral Makarov Street 10, Moscow 125212, Russia Davydkin V.Yu. G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology, Admiral Makarov Street 10, Moscow 125212, Russia KIimova E.V. Moscow State University of Fine Chemical Technologies named after M.V. Lomonosov, 86, Prospekt Vernadskogo, 119571, Moscow, Russia DOI: 10.31618/asj.2707-9864.2021. 1.56. 142 Abstract. The overview focuses on our own data on the use of water-soluble glycoconjugates (www.lectinity.com) based on a linear polyacrylamide chain in relation to recombinant therapeutic human protein hormones and probiotic recognition proteins such as enzymes and lectins. The results obtained characterize the basic principles of multilevel relationships between proteins and glycoconjugates, including the assembly of complexes and nanoparticles on the solid phase. Prospects for the application of these principles and cases of interaction of proteins and glycoconjugates, including taking into account the participation of enzymes, in the study of human proteins and viruses, are noted. The presented data can help in development of the protective network communication systems as well as new combined preparations against infections and pathogens. These data can serve the keys to be applied in medical biotechnology. Аннотация. В обзоре основное внимание уделяется собственным данным об использовании водорастворимых гликоконъюгатов (www.lectinity.com ) на основе линейной полиакриламидной цепи по отношению к рекомбинантным терапевтическим белковым гормонам человека и пробиотическим белкам распознавания, таким как ферменты и лектины. Полученные результаты характеризуют основные принципы многоуровневых взаимоотношений между белками и гликоконъюгатами, включая сборку комплексов и наночастиц на твердой фазе. Отмечены перспективы применения указанных принципов и случаев взаимодействия белков и гликоконъюгатов, в том числе с учетом участия ферментов, при изучении белков и вирусов человека, в том числе в аспекте борьбы с инфекциями и патогенами. Представленные данные могут помочь в разработке защитных сетевых коммуникационных систем, а также новых комбинированных препаратов против патогенов. Эти данные могут послужить ключом к применению в медицинской биотехнологии и в будущем.
Actor Loss of Soft Actor Critic Explained

This technical report is devoted to explaining how the actor loss of soft actor critic is obtained, as well as the associated gradient estimate. It gives the necessary mathematical background to derive all the presented equations, from the theoretical actor loss to the one implemented in practice. This necessitates a comparison of the reparameterization trick used in soft actor critic with the nabla log trick, which leads to open questions regarding the most efficient method to use.
A Critical Review of Inductive Logic Programming Techniques for Explainable AI

Despite recent advances in modern machine learning algorithms, the opaqueness of their underlying mechanisms continues to be an obstacle in adoption. To instill confidence and trust in artificial intelligence (AI) systems, explainable AI (XAI) has emerged as a response to improve modern machine learning algorithms' explainability. Inductive logic programming (ILP), a subfield of symbolic AI, plays a promising role in generating interpretable explanations because of its intuitive logic-driven framework. ILP effectively leverages abductive reasoning to generate explainable first-order clausal theories from examples and background knowledge. However, several challenges in developing methods inspired by ILP need to be addressed for their successful application in practice. For example, the existing ILP systems often have a vast solution space, and the induced solutions are very sensitive to noises and disturbances. This survey paper summarizes the recent advances in ILP and a discussion of statistical relational learning (SRL) and neural-symbolic algorithms, which offer synergistic views to ILP. Following a critical review of the recent advances, we delineate observed challenges and highlight potential avenues of further ILP-motivated research toward developing self-explanatory AI systems.
ViNMT: Neural Machine Translation Toolkit

We present an open-source toolkit for neural machine translation (NMT). The new toolkit is mainly based on vaulted Transformer (Vaswani et al., 2017) along with many other improvements detailed below, in order to create a self-contained, simple to use, consistent and comprehensive framework for Machine Translation tasks of various domains. It is tooled to support both bilingual and multilingual translation tasks, starting from building the model from respective corpora, to inferring new predictions or packaging the model to serving-capable JIT format.
Social Neuro AI: Social Interaction as the “Dark Matter” of AI

This article introduces a three-axis framework indicating how AI can be informed by biological examples of social learning mechanisms. We argue that the complex human cognitive architecture owes a large portion of its expressive power to its ability to engage in social and cultural learning. However, the field of AI has mostly embraced a solipsistic perspective on intelligence. We thus argue that social interactions not only are largely unexplored in this field but also are an essential element of advanced cognitive ability, and therefore constitute metaphorically the “dark matter” of AI. In the first section, we discuss how social learning plays a key role in the development of intelligence. We do so by discussing social and cultural learning theories and empirical findings from social neuroscience. Then, we discuss three lines of research that fall under the umbrella of Social NeuroAI and can contribute to developing socially intelligent embodied agents in complex environments. First, neuroscientific theories of cognitive architecture, such as the global workspace theory and the attention schema theory, can enhance biological plausibility and help us understand how we could bridge individual and social theories of intelligence. Second, intelligence occurs in time as opposed to over time, and this is naturally incorporated by dynamical systems. Third, embodiment has been demonstrated to provide more sophisticated array of communicative signals. To conclude, we discuss the example of active inference, which offers powerful insights for developing agents that possess biological realism, can self-organize in time, and are socially embodied.