Miracle-dz/UniFAR-FTUs huggingface dataset:
Maxillo-facial and neck surgery in Iraq and Afghanistan

ver the past 150 years, military personnel wounded in action had a survival rate of approximately 80% [1]. During the current conflicts in Iraq and Afghanistan, those servicemen wounded in action have a 90.4% survival rate [2]. During the past 10 years in Iraq and Afghanistan, more than 7000 American military personnel have been treated for head and neck injuries at American medical facilities in both war zones [3]. The multispecialty head and neck surgical teams treating the maxillo-facial injury (MFI) patients include neurosurgeons, otolaryngologists-head and neck surgeons, oral maxillo-facial surgeons, and ophthalmologists [4]. Valuable head and neck trauma lessons applicable to military and civilian practice were learned in Iraq and Afghanistan.
Link prediction via community detection in bipartite multi-layer graphs

The growing number of multi-relational networks pose new challenges concerning the development of methods for solving classical graph problems in a multi-layer framework, such as link prediction. In this work, we combine an existing bipartite local models method with approaches for link prediction from communities to address the link prediction problem in multi-layer graphs. To this end, we extend existing community detection-based link prediction measures to the bipartite multi-layer network setting. We obtain a new generic framework for link prediction in bipartite multi-layer graphs, which can integrate any community detection approach, is capable of handling an arbitrary number of networks, rather inexpensive (depending on the community detection technique), and able to automatically tune its parameters. We test our framework using two of the most common community detection methods, the Louvain algorithm and spectral partitioning, which can be easily applied to bipartite multi-layer graphs. We evaluate our approach on benchmark data sets for solving a common drug-target interaction prediction task in computational drug design and demonstrate experimentally that our approach is competitive with the state-of-the-art.
The Functional Consequences of Eukaryotic Topoisomerase 1 Interaction with G-Quadruplex DNA

Topoisomerase I in eukaryotic cells is an important regulator of DNA topology. Its catalytic function is to remove positive or negative superhelical tension by binding to duplex DNA, creating a reversible single-strand break, and finally religating the broken strand. Proper maintenance of DNA topological homeostasis, in turn, is critically important in the regulation of replication, transcription, DNA repair, and other processes of DNA metabolism. One of the cellular processes regulated by the DNA topology and thus by Topoisomerase I is the formation of non-canonical DNA structures. Non-canonical or non-B DNA structures, including the four-stranded G-quadruplex or G4 DNA, are potentially pathological in that they interfere with replication or transcription, forming hotspots of genome instability. In this review, we first describe the role of Topoisomerase I in reducing the formation of non-canonical nucleic acid structures in the genome. We further discuss the interesting recent discovery that Top1 and Top1 mutants bind to G4 DNA structures in vivo and in vitro and speculate on the possible consequences of these interactions.
Taming the 'Alpha-Male' In the Space Between Art and Business

Arts-based interventions may expand how team members and leaders understand their roles and impact. For an intervention to be useful, there needs to be a way for the aesthetic experience to translate back into the regular organisation. Nine managers of a professional services firm, including the chief executive, engaged in weekly group singing sessions for more than a year. The paper discusses their learnings in light of the two communities of practice they took part in—the choir practice and the managerial practice. In terms of learning content, the notion of “alpha-male” serves a label for the range of identities and behaviours that were rattled. The aesthetic experience of multi-part choral singing enabled the participants to hear the futility of being constantly pushy. Eventually a more varied team dynamics emerged. The paper focuses on one particular aspect of the set-up—the location of the practices and the transfer space between them. The stair-case connecting the two practices became an in-between space—a conduit—where the aesthetic experience lingered, was interpreted, and applied, in silence or through dialogue.
Identifying Cancerous Tissues Using Dynamic Neural Network with Reuse

: In this paper we present a system to identify the cancerous tissues using Hopfield based Dynamic Neural Network. The DNN has a composite structure consisting of several basic nodes. The basic nodes are completely connected Hopfield networks and they are similar to each other. The DNN with relative pruning and reuse is used for the present task as it is having the properties like associative memory with 100% recall, large storage capacity, avoiding spurious states and converging only to user specified states. Since the DNN with reuse operates with binary data while the information in Cancer Database is in decimal form, the decimal digits are mapped a binary string called descriptor. The network is trained by descriptors (binary strings), which are obtained through the steps indexing through thresholding. These descriptors are used as exemplar patterns to store them in the DNN with reuse by training. The associative memory property of the network makes it to recall a closest pattern of the given query pattern among the memorized patterns. The experimental results show that the percentage of accurately identifying a cancerous person depends on the length of descriptor.
Improving the Speed of Peer to Peer Backup Systems with BitTorrent

For many computer users, having access to a reliable file backup service is important. As computers and computer-related technologies improve, users have the ability to generate higher resolution content. Creating backups becomes less feasible as the amount of data grows; limited network bandwidth makes the backup process cumbersome, and access to a large amount of storage space for backups is either limited or expensive. In this report, we propose a new backup system, BTBackup, which aims to solve both problems. Our system is designed as a Peer-to-Peer (P2P) network, where users of the system use each other as backup locations. Users offer storage space that is proportional to the amount of data that they back up. This means that the capacity of each user’s physical storage is the only limiting factor for how much they can back up. We solve the problem of long data transfers for big files by leveraging the speed offered by the BitTorrent protocol, which uses a file chunking mechanism to download files from multiple peers at once. By testing our system in various scenarios, we show that it achieves our goal of quicker backup creation and recovery through the use of file transfer parallelization.
Secondary Principals' Perspectives on the Impact of Work Intensification on the Secondary Vice-Principal Role

Principals’ work intensification has increased the volume and complexity of their daily tasks. This exploratory study was conducted to determine how secondary principals’ work intensification has influenced their understanding of the secondary vice-principal role. Thirteen secondary principals from Ontario, Canada participated in one-time semi-structured interviews for this qualitative study. Findings indicate that secondary principals expect their vice-principals to perform both operational and instructional tasks, although the work completed by secondary vice-principals remains predominantly school operations. Duties are determined collaboratively as a school administrative team. Three tensions emerged regarding how secondary principals perceive the secondary vice-principal role: They believe their vice-principals (i) experience role conflict and role ambiguity, (ii) have difficulty prioritising operational and instructional duties, and (iii) have difficulty achieving work–life balance. Recommendations to professional practice, educational policy, and research in educational leadership are included.
EVALUATION OF THE PHOTOCATALYTIC ACTIVITY OF SiO2@TiO2 HYBRID SPHERES IN THE DEGRADATION OF METHYLENE BLUE AND HYDROXYLATION OF BENZENE: KINETIC AND MECHANISTIC STUDY

Silica spheres coated with titania (SiO2@TiO2) were synthesized using chitosan as template. The N2 adsorption/desorption isotherms of the spheres point to meso and macroporous characteristics and the elemental mapping by EDS shows uniform distribution of Ti on the surface of the silica spheres, leading to formation of an amorphous structure (XRD). The results from the model reaction of photocatalytic degradation of methylene blue (MB) show a good stability of the spheres regarding their reuse. The tests with various additives pointed to hydroxyl radical production as the main via of MB degradation. The photocatalytic activity of the spheres in the hydroxylation of benzene to form phenol, hydroquinone and benzoquinone was assessed. The kinetic data point to the formation of phenol as the limiting step; in addition, the phenol consumption occurs by parallel and consecutive reactions producing benzoquinone.
Summarizing Dynamic Graphs using MDL

How can we succinctly describe a large, dynamic graph over time? Given a large dynamic graph, can we ﬁnd “important” patterns that evolve over time, so that we can easily summarize and visualize it? In real life, these patterns signify interaction between nodes over time - for example, how the network traﬃc of a bank changes during the day, how calling patterns change season over season, or how people watch different genre of movies over diﬀerent times of the year. Our work focuses on the problem of how we ﬁnd and rank these patterns. To this end, we formalize this problem as minimizing the encoding cost in a data compression paradigm and propose Mango , an eﬀective heuristic for ﬁnding evolving patterns in dynamic graphs. We then apply our method to synthetic datasets and dblp and show that Mango is able to summarize dynamic graphs by ﬁnding meaningful static and temporal patterns. This work is currently in progress and we are evaluating performance on real world datasets. We are sharing preliminary evaluation on a few synthetic datasets and a popular real-world dataset, dblp .
Innovation and patterns in extreme firm growth and decline

A noteworthy stylized fact that has emerged recently in the literature on firm growth is that both among firms on the upper tail and firms on the lower tail of the short run firm growth rate distribution, from one year to the next, some persist, while significant proportions bounce to the opposite tail. We find that innovation plays an important role in generating this pattern in firm growth. Innovation, in terms of its component stages, increase both the probability of sustaining or rebounding to extreme positive growth, and the probability of sustaining or bouncing down to extreme negative decline, with the former dominating the latter. Potential rewards of innovation are highest for firms that are growing most rapidly. These findings have important implications for
Asymmetric Business Cycles in Segmented Labour Markets

We document the presence of asymmetric business cycles in both regular and contract labour markets in India and investigate the role of nominal wage rigidities and labour adjustment costs in accounting for these asymmetries. Using data from Annual Survey of Industries, we find that (i) the growth rate of output is negatively skewed, (ii) the growth of regular employment is negatively skewed while that of contract employment is positively skewed, (iii) the nominal wage growth of regular workers is positively skewed while that of contract workers is negatively skewed. We show that a standard business cycle model augmented with asymmetric wage adjustment cost for both regular and contract labour coupled with symmetric labour adjustment cost for regular workers does a good job of explaining the asymmetries in both output and employment cycles. We also find that the presence of contract labour relaxes the constraint of downward nominal wage rigidity, and hence decreases the optimal level of grease inflation required in the economy.
The E¤ect of Household Appliances on Female Labor Force Participation: Evidence from Micro Data

We estimate the e¤ect of household appliance ownership on the labor force participation rate of married women using micro-level data from the 1960 and 1970 U.S. Censuses. In order to identify the causal e¤ect of home appliance ownership on married womens labor force participation rates, our empirical strategy exploits both time-series and cross-sectional variation in these two variables. To control for endogeneity, we instrument a married womans ownership of an appliance by the average ownership rate for that appliance among single women living in the same U.S. state. Single womens labor force participation rates did not increase between 1960 and 1970. We nd evidence in support of the hypothesis that the di¤usion of household appliances contributed to the increase in married womens labor force participation rates during the 1960s. Keywords: Female labor supply, household appliances, home production. JEL Classi cation: J22. Thanks without implication to Bill Evans, David deJong, Finn Kydland, Marla Ripoll, Holger Sieg, Fallaw Sowell, and seminar participants at MIT, the University of Pittsburgh, the 2008 Midwest Macro Meetings in Philadelphia, and the 2008 SED meetings in Boston, for helpful comments. Thanks also to the Editor of this journal (Philip Oreopoulos) and two anonymous referees for helpful suggestions and comments. yCorresponding author. Fax: 1-412-268-7064. Phone: 1-412-268-6143.
FURTHER DIFFERENTIATING ITEM AND ORDER 3 Further Differentiating Item and Order Information in Semantic Memory : Students ’ Recall of Words from the “ CU Fight Song

University of Colorado (CU) students were tested for both order and item information in their semantic memory for the “CU Fight Song. ” Following an earlier study by Overstreet and Healy (2011), a symmetrical bow-shaped serial position function (with both primacy and recency advantages) was found for reconstructing the order of the 9 lines in the song, whereas a function with no primacy advantage was found for recalling a missing word from each line. This difference between order and item information was found even though students filled in missing words without any alternatives provided and missing words came from the beginning, middle, or end of each line. Similar results were found for CU students’ recall of the sequence of Harry Potter book titles and the lyrics of the Scooby Doo theme song. These findings strengthen the claim that the pronounced serial position function in semantic memory occurs largely because of the retention of order, rather than item, information.
Polyketide Synthesized Pigment Regulated by Histone Deacetylase in Penicillium chrysogenum

The Pc21g14570 gene of Penicillium chrysogenum encodes an ortholog of a class 2 histone deacetylase termed HdaA which may play a role in epigenetic regulation of secondary metabolism. Deletion of the hdaA gene induces a significant pleiotropic effect on the expression of a set of polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) encoding genes. The hdaA deletion mutant exhibits a decreased conidial pigmentation that links to a reduced expression of the PKS gene Pc21g16000 (pks17) responsible for the production of the conidial pigment precursor naphtha-γ-pyrone. Moreover, the hdaA deletion caused decreased levels of the yellow pigment chrysogine that could be associated with the down regulation of the NRPS encoding gene Pc21g12630 and neighboring genes that are part of a cluster. In addition, transcriptional activation of an unknown PKS gene cluster containing Pc21g05070 (pks12) and Pc21g05080 (pks13) occurred. However, these genes already acquired single nucleotide substitutions at early stages of the classical strain improvement of P. chrysogenum for β-lactam production that likely inactivated their activities and thus no specific metabolites could be detected. Our present results suggest that an epigenomic approach can be successfully applied for the activation of secondary metabolism in P. chrysogenum. 4 4.
OP-VEVO180037 1..12

The Coronaviridae family of viruses encompasses a group of pathogens with a zoonotic potential as observed from previous outbreaks of the severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus. Accordingly, it seems important to identify and document the coronaviruses in animal reservoirs, many of which are uncharacterized and potentially missed by more standard diagnostic assays. A combination of sensitive deep sequencing technology and computational algorithms is essential for virus surveillance, especially for characterizing novelor distantly related virus strains. Here, we explore the use of profile Hidden Markov Model-defined Pfam protein domains (Pfam domains) encoded by new sequences as a Coronaviridae sequence classification tool. The encoded domains are used first in a triage to identify potential Coronaviridae sequences and then processed using a Random Forest method to classify the sequences to the Coronaviridae genus level. The application of this algorithm on Coronaviridae genomes assembled from agnostic deep sequencing data from surveillance of bats and rats in Dong Thap province (Vietnam) identified thirty-four Alphacoronavirus and eleven Betacoronavirus genomes. This collection of bat and rat coronaviruses genomes provided essential information on the local diversity of coronaviruses and substantially expanded the number of coronavirus full genomes available from bat and rats and may facilitate further molecular studies on this group of viruses.
The Shadow Education System: Students’ Responses to Private Tutorial Learning

Purpose - In Malaysia, many families devote a portion of their income to private tutorial learning fees. Many parents, especially those who stay in urban areas, send their children for private tutorial learning. This research investigated the challenges of a shadow education system by analysing Malaysian secondary school students’ reactions to private tutorial learning. Methodology - A survey instrument with a structured questionnairewas designed on a webpage and delivered via email and Virtual Learning Environment through Frog Asia, which is the first company to connect Malaysian schools through a single cloud-based learning platform. The online survey approach was chosen as a convenient and cost effectiveness means of interacting with respondents who were dispersed in various geographical locations across the country. 148 respondents from three Malaysian states, Penang, Perak and Johor, were identified using convenience sampling. Findings - The results showcase the reasons for choosing private tutoring from both students’ and parents’ perspective. Significant findings revealed that the factors influencing students’ choice to attend private tutorial learning were the school environment, social influence, rigidity of the school system, students’ learning attitude and affordability for parents. The study also indicated that parents were exercising excessive force on students’ academic choices, which increased tension and anxiety among their children. Parental influence can be stressful and have a traumatic impact on children’s learning abilities. Furthermore, it was found that students were missing extra-curricular activities. Significance - The secondary school syllabus is too crammed and its scope is too wide, leading school teachers to complete it without in-depth teaching and learning activities. Due to peer influence, private tuition becomes a routine activity, causing school students to miss extra-curricular activities. Ultimately, a good outgoing school student is a potential candidate for higher education, and educationally qualified and skilled persons are needed for the future economy of Malaysia. It is suggested that education policy makers should not introduce a rigid curriculum as rigidity leads to rote learning and produces poorly talented children.
Timing of renal replacement therapy for patients with acute kidney injury: A systematic review and meta-analysis

Background Acute kidney injury is associated with high mortality, and the optimal time to start renal replacement therapy for acute kidney injury is unknown despite several randomised controlled trials on the subject. We performed a systematic review and meta-analysis to assess the effect of earlier initiation of renal replacement therapy for acute kidney injury on mortality and reported secondary outcomes. Methods All literature in databases EMBASE, MEDLINE and CENTRAL was searched from January 1970 to March 2019 using terms related to renal replacement therapy, timing and randomised controlled trials. All randomised controlled trials with 25 or more adult participants suffering from acute kidney injury comparing timing of renal replacement therapy were included. The results of the selected studies were pooled and expressed in terms of risk ratios (RR) and 95% confidence intervals (95% CI) using a random effects model. Results A total of 7008 records were identified; 94 were selected for full text review of which 10 were included in the final meta-analysis. The 10 studies comprised 1956 participants (989 ‘early’ group; 967 ‘late’ group) with 918 total deaths; the analysis demonstrated no significant differences between the ‘early’ and ‘late’ renal replacement therapy groups (RR = 0.98 (95% CI = 0.84, 1.15)) for mortality. No significant differences between groups were evident for period-wise mortality; dialysis dependence; recovery of renal function; length of intensive care unit or hospital stay; or number of renal replacement therapies, mechanical ventilation and vasopressor-free days. Conclusions Current evidence does not support the use of early renal replacement therapy for patients with acute kidney injury. Data from ongoing and future randomised controlled trials are required to strengthen the evidence base in the area.
Minimization of Network Induced Jitter Impact on FPGA-Based Control Systems for Power Electronics through Forward Error Correction

In modular distributed architectures, the adoption of a communication method that is at the same time robust and has a low and predictable latency is of utmost importance in order to support the required system dynamics. The aim of this paper is to evaluate the consequences of the random jitter on machine drives distributed control, caused by the messages’ re-transmission in case of an error in the received data. To achieve this goal, two different Forward Error Correction (FEC) techniques are introduced in the chosen protocol, so that the recipient of the message can correct random errors without the need of any additional round trip delays needed to request and obtain a re-transmission. Experimentally validated simulations are used to evaluate the impact of random network derived jitter on a real world closed loop control system for distributed power electronic converters.