Miracle-dz/UniFAR-FTUs huggingface dataset:
The emerging roles of E3 ubiquitin ligases in ovarian cancer chemoresistance

Epithelial cancer of the ovary exhibits the highest mortality rate of all gynecological malignancies in women today, since the disease is often diagnosed in advanced stages. While the treatment of cancer with specific chemical agents or drugs is the favored treatment regimen, chemotherapy resistance greatly impedes successful ovarian cancer chemotherapy. Thus, chemoresistance becomes one of the most critical clinical issues confronted when treating patients with ovarian cancer. Convincing evidence hints that dysregulation of E3 ubiquitin ligases is a key factor in the development and maintenance of ovarian cancer chemoresistance. This review outlines recent advancement in our understanding of the emerging roles of E3 ubiquitin ligases in ovarian cancer chemoresistance. We also highlight currently available inhibitors targeting E3 ligase activities and discuss their potential for clinical applications in treating chemoresistant ovarian cancer patients.
Discovering Non-monotonic Autoregressive Orderings with Variational Inference

The predominant approach for language modeling is to process sequences from left to right, but this eliminates a source of information: the order by which the sequence was generated. One strategy to recover this information is to decode both the content and ordering of tokens. Existing approaches supervise content and ordering by designing problem-specific loss functions and pre-training with an ordering pre-selected. Other recent works use iterative search to discover problem-specific orderings for training, but suffer from high time complexity and cannot be efficiently parallelized. We address these limitations with an unsupervised parallelizable learner that discovers high-quality generation orders purely from training data -- no domain knowledge required. The learner contains an encoder network and decoder language model that perform variational inference with autoregressive orders (represented as permutation matrices) as latent variables. The corresponding ELBO is not differentiable, so we develop a practical algorithm for end-to-end optimization using policy gradients. We implement the encoder as a Transformer with non-causal attention that outputs permutations in one forward pass. Permutations then serve as target generation orders for training an insertion-based Transformer language model. Empirical results in language modeling tasks demonstrate that our method is context-aware and discovers orderings that are competitive with or even better than fixed orders.
Malaria prevention and treatment awareness and practice among patent medicine vendors (PMVs) in Gombe Metropolis, Nigeria

The ravaging consequences of Malaria in Sub-Saharan Africa (SSA) have been a subject of serious concern to every stakeholder. Literature and anecdotal evidence shows that around 60% of Nigerians seek fever treatment from Patent Medicine Vendors (PMVs) despite the limited formal dispensing knowledge most possess. This study attempts to establish a base line of knowledge, attitude and practices of Malaria control among PMVs in Gombe Metropolis, North Eastern Nigeria. The study was a descriptive cross sectional survey based on structured questionnaires used to collect relevant information from 109 PMVs selected by purposive sampling technique. The result show that 85.3% of the participants in this study correctly identified fever or high body temperature as the common sign of uncomplicated (UC) Malaria, while 70.6% recognized convulsion as one of the main symptoms of severe Malaria. Furthermore, 86.2% of the PMVs also knew that sleeping inside treated nets constitute one of the best ways to prevent Malaria. In the same vein, awareness of change in Malaria treatment policy from monotherapy to Artemisinin based combination therapy (ACT) was high (73.3%) among them. However, those PMVs that had ever undergone some degree of drug dispensing training exhibited a significantly higher level of awareness of change in malaria treatment policy (X2 =17.903, P = 0.000). Although 85.3% of PMVs frequently recommend Arthemeter Lumefantrine (AL) as treatment of uncomplicated Malaria, only 39.4% of the participants would refer severe malaria cases. Even though most Malaria control awareness and practice variables were found to be fairly good among the participants, it is clear from the study that there is the need for enhanced training, monitoring and supervision by the relevant authorities so as to fully harness the vast potential in PMVs.
Integration of High Velocity Elastic Band for Hamstring Training in Pre-Season Routine of Football Players

Background. A need for other methods of hamstring strengthening are thus warranted with the main aim of reducing the risk of injury during the subsequent intense athletic activities. The study aimed to examine changes in hamstring strength in response to high velocity elastic band training when incorporated into regular training routine of football players. Methods. Research participants were professional top level football players (age 23.1 ± 5.7 years; weight 77.2 ± 7.7 kg, training experience 14.1 ± 5.8 years). In the pre-season, in addition to their routine training, the experimental group performed hamstring curls at maximal intensity while lying prone three times per week for five weeks, while control group continued their routine training. Concentric knee torque at 60°/s and 180°/s angular velocities, countermovement jump height, 30m sprint running performance from standing and flying start, and knee flexion-extension movement frequency were measured before and after the 5 weeks of training. Results. Hamstring curl frequency during lying prone increase by 10.5 % (p .05). Conclusion. High velocity elastic band training incorporated into regular pre-season routine is beneficial for football players to increase their knee extension-flexion maximal movement frequency with no evident effects on strength, jump and sprint running performance. Results might be related with concurrent training during preparatory training phase of the pre-season when several physical capacities are being developed simultaneously. Keywords: high speed movements; peak torque; sprint performance; prevention of hamstring injuries; knee flexion strength.
Relationship between Periodontitis and Psychosocial Impact in Patients with Systemic Sclerosis: A Clinical Study

Background: Systemic Sclerosis (SSc) is a multi-system disorder that can have significant adverse effects upon the oral health. The aim of this study was to analyze the associations between SSc, periodontal disease (PD) and tooth loss and oral health-related quality of life (OHRQoL). Methods : For the study were enrolled 70 patients affected by SSc and 75 non-diseased controls matched for age and gender. SSc was characterized in subtypes and with the mean duration of disease and the Modified Rodnan Skin Score [mRSS]. Patients were surveyed and examined through the evaluation of the periodontal parameters and the number of teeth and OHRQoL scores. Results : A logistic regression analysis showed that patients with SSc presented a higher number of missing teeth (p=0.001) and a 6.89-fold (95% CI 2.04 to 18.36) increased odds of CAL compared to the control group. Moreover, the less values of PPD was correlated with mRSS in the total SSc group and with the mean duration of disease in patients with limited SSc, even after adjusting this correlation with the presence of the major organ involvement. The OHIP sub-scale psychosocial impact differed significantly between groups (p= 0.002). The OHIP sum score was also significantly different between groups (p< 0.001). Conclusions : This study showed that patients with SSc presented an increased odds of PD and tooth loss compared to non-diseased controls. In SSc patients, the magnitude of PD was strongly associated with the mRSS and with the mean duration of the disease.
PHOTOCATALYTIC REDUCTION OF CARBON DIOXIDE IN GAS STEAMS BY UV/TiO2 PROCESS

The reduction of carbon dioxide in gas streams by UV/TiO2 process was studied in a flow reactor under various retention time, humidity contents, initial carbon dioxide concentrations, and UV light intensities. TiO2 particles were used as photocatalyst and impregnated on the non-woven fabric textile for the reduction of carbon dioxide in gas streams under the irradiation of 365 nm UV light. The primary products from carbon dioxide reduction were determined to be methane and methanol. The photocatalytic reduction rate of carbon dioxide was found to be increased linearly with increasing initial of carbon dioxide concentration and can be well described by a LangmuirHinshelwood type rate equation suggesting that the adsorption of CO2 on TiO2 is the ratedetermining step. The reduction rate of gaseous carbon dioxide was increased with increasing humidity content present in the gas stream for experiments conducted with humidity less than 55%. However, the reduction rate was decreased with increasing humidity content for experiments conducted with the presence of more than 55% humidity. Combing the equations of continuity and surface catalyst kinetics, a quasi-global kinetic model is developed for modeling the reduction of carbon dioxide by UV/TiO2 process at various operation conditions.
First, Do No Harm: Studying the manipulation of security headers in browser extensions

—Browser extensions are add-ons that aim to enhance the functionality of native Web applications on the client side. They intend to provide a rich end-user experience by leveraging feature-rich privileged JavaScript APIs, otherwise inaccessible for native applications. However, numerous large-scale investigations have also reported that extensions often indulge in malicious activities by exploiting access to these privileged APIs such as ad injection, stealing privacy-sensitive data, user ﬁngerprinting, spying user activities on the Web, and malware distribution. In this work, we instead focus on tampering with security headers. To that end, we analyze over 186K Chrome extensions, publicly available on the Chrome Web Store, to detect extensions that actively intercept requests and responses and tamper with their security headers by either injecting, dropping, or modifying them, thereby undermining the security guarantees that these headers typically provide. We propose an automated framework to detect such extensions by leveraging a combination of static and dynamic analysis techniques. We evaluate our proposed methodology by investigating the extensions’ behavior against Tranco Top 100 domains and domains targeted explicitly by the extensions under test and report our ﬁndings. We observe that over 2.4K extensions actively tamper with at least one security header, undermining the purpose of the server-delivered, client-enforced
A high mountain lizard from Peru: The world’s highest-altitude reptile

Life at high altitudes is particularly challenging for ectothermic animals like reptiles and involves the evolution of specialised adaptations to deal with low temperatures, hypoxia and intense UV radiation. As a result, only very few reptile taxa are able to survive above 5,000 m elevation and herpetological observations from these altitudes are exceedingly rare. We report here an exceptional observation of a lizard population (Liolaemus aff. tacnae; Reptilia, Squamata) from the high Andes of Peru. During an ascent of Chachani mountain (6,054 m, 16°11'S, 71°32'W), we observed and documented photographically this species living between 5,000 and 5,400 m above sea level. Following a review of literature, we show that this is the highest known record of a reptile species.
Detection of icaA Gene Expression in Clinical Biofilm-Producing Staphylococcus Aureus Isolates

The pathogenicity resulting from Staphylococcus aureus infection has remarkable importance as one of the community-associated bacterial infections, due to the virulent ability of these bacteria to produce biofilms. This study was designed to detect biofilm production in clinical isolates from samples of wounds and urinary tract infections. The expression levels of the icaA gene that is responsible of slime layer production in biofilms was compared in isolates with different biofilm producing capabilities. Fifty seven samples that included 32 samples from urine and 25 samples from wounds were collected from Alwasti Hospital, Al-Kindi Teaching Hospital, and Alzahraa Clinic, Baghdad, Iraq. The bacteria was identified according to biochemical tests, API20 strip test, and PCR assay. The results of 16S rRNA PCR detection revealed that nine isolates were identified as S. aureus. The biofilm assay showed that 46.15% of the isolates were strong biofilm producers, 46.15% had moderate ability to produce biofilm, and 7.70% were weak producers. Quantitative PCR assay was carried out on three isolates with different biofilm-producing abilities. The results demonstrated that the strong biofilm-producing isolates had significantly higher (P â‰¤0.01) gene expression level (6.508) compared with the moderate (1.624) and the weak (1.231) isolates.
Ultrafast light induced dynamics of Xe nanoparticles studied with a combination of intense infrared and x-ray pulses

With the advent of the X-ray free electron laser (FEL) technology resulting in extremely intense and femtosecond short X-ray flashes, the diffraction imaging of nonperiodic nanosamples with a single X-ray FEL pulse is within reach. As all matter, the nanoparticle irradiated by the intense FEL pulse with power densities up to 1017 W/cm2 is damaged though ionization within femtoseconds and later explodes. Thus, the resolution and the quality of the X-ray image is limited through the disintegration of the nanoparticle initiated during the imaging process. The present work explores the expansion dynamics of the nanosample and the influence of the nanosample damage on the diffraction image. A significant strucural damage of the nanosample on a sub-ps time scale was observed. The disintegration of the particle could be reconstructed from the diffraction pattern. The experiments were performed at the Linac Coherent Light Source (LCLS), the first X-ray FEL. In the present study a two color pump-probe scheme was implemented for time-resolved experiments on large Xe rare gas clusters with ⟨N⟩ = 105 − 106 atoms as samples. The work is separated into two parts. In the first part, an IR laser pulse with up to 1015 W/cm2 power density damaged the clusters and initiated a cluster explosion. The damage dynamics of the nanosample was imaged by a delayed FEL pulse. The recorded X-ray scattering pattern showed a signal decrease in high scattering angles 250 fs after the IR laser pulse arrival. The resulting X-ray scattering pattern could be reconstructed using a non-uniform cluster expansion model developed in the present work. In the second part, the pump-probe scheme was reversed. The FEL pulse imaged clusters were probed by the delayed IR laser pulse. The absorption from the IR laser depends on the expansion stage of the nanosample. Thus, the FEL induced explosion dynamics could be reconstructed from the IR laser-cluster interaction products. A significant expansion of the clusters around one picosecond was detected for incident FEL photon fluxes 1014 − 1017 W/cm2. The expansion time scales were confirmed by a quasi-equilibrium model developed in this work.
THE DEPTH DISTRIBUTION OF BERYLLIUM 7 IN THE SOIL STUDY

The main objective of this study is to examine the depth distribution of 7Be in the soil . The study was conducted in an open land area in Bangi, Selangor during the two (2) month rainy season in 2016. All soil core samples taken by using metal corer and brought to Radiochemistry and Environment Group Laboratory (RAS), Malaysian Nuclear Agency for further treatment. All samples have been sectioned into 2 mm increments to a depth of 4 cm and subsequently, oven dried at 4560 oC and gently disaggregated. The sample is passed through a < 2 mm sieve and packed into geometry plastic container for 7Be analysis using gamma spectrometry with a 24-hour count time. Based on the analysis results obtained, the concentration of 7Be is deposited into decreases exponentially with depth, is confined within the top few centimeters at most and similar with other works been reported for all samples. However, a detailed study that is by increasing the number of sampling stations throughout Peninsular Malaysia should be done in ensuring a complete data for a future reference.
Über die vermeintliche Isomerie des roten und gelben Quecksilberoxyds und die Oberflächenspannung fester Körper

Die von mir aus den thermochemischen Messungen von V a r e t und den elektrischen und chemischen von Tb. Mark 1 ) gezogene Schlussfolgerung, dass zwischen rotem und gelbem Quecksilberoxyd kein anderer Unterschied als der der Korngrösse besteht, ist im vorigen Jahre von E. Cohen 8 ) auf Grund seines Befundes, dass zwischen beiden eine Verschiedenheit der elektromotorischen Kraft von 0-685 Millivolt beobachtet werden kann, in sehr bestimmten Ausdrücken für irrtümlich erklärt worden. Bei Gelegenheit einer persönlichen Begegnung machte ich Herrn C o h e n aufmerksam, dass der von ihm beobachtete kleine Unterschied der elektromotorischen Kraft mit der von mir gegebenen Deutung keineswegs im Widerspruche steht, da nach bekannten Prinzipien ein feines Pulver löslicher sein muss als ein grobes, ebenso wie kleine Tröpfchen einen grösseren Dampfdruck haben als grosse. Diese aus der Lehre von Oberflächenenergie zu ziehende Schlussfolgerung ist ja qualitativ seit langem durch die bekannte Kornvergrösserung belegt, welche feinpulverige Körper im Laufe der Zeit unter ihrer gesättigten Lösung erleiden. Doch scheint diese Überlegung von Herrn C o h e n nicht für zutreffend gehalten worden zu sein, da er in dieser Zeitschrift) seine oben erwähnte Arbeit nochmals zum Abdruck hat bringen lassen. Um nicht den Irrtum entstehen zu lassen, als halte ich die Ansicht von der Isomerie der beiden Quecksilberoxyde durch jene an sich ganz sorgfaltigen und in gewissem Sinne richtigen Messungen für bewiesen, gestatte ich mir, einige Beobachtungen mitzuteilen, die mit jener Ansicht durchaus nicht übereinstimmen, während sie mit der von mir früher ausgesprochenen in völligem Einklänge stehen.
Finite-difference modeling of 2-D wave propagation in the vicinity of dipping interfaces: a comparison of anti-aliasing and equivalent medium approaches

Finite-difference (FD) modeling of seismic waves in the vicinity of dipping interfaces gives rise to artifacts. Examples are phase and amplitude errors, as well as staircase diffractions. Such errors can be reduced in two general ways. In the first approach, the interface can be anti-aliased (i.e., with an anti-aliased step-function, or a lowpass filter). Alternatively, the interface may be replaced with an equivalent medium (i.e., using Schoenberg \&Muir (SM) calculus or orthorhombic averaging). We test these strategies in acoustic, elastic isotropic, and elastic anisotropic settings. Computed FD solutions are compared to analytical solutions. We find that in acoustic media, anti-aliasing methods lead to the smallest errors. Conversely, in elastic media, the SM calculus provides the best accuracy. The downside of the SM calculus is that it requires an anisotropic FD solver even to model an interface between two isotropic materials. As a result, the computational cost increases compared to when using isotropic FD solvers. However, since coarser grid spacings can be used to represent the dipping interfaces, the two effects (an expensive FD solver on a coarser FD grid) equal out. Hence, the SM calculus can provide an efficient means to reduce errors, also in elastic isotropic media.
Bayesian matrix completion with a spectral scaled Student prior: theoretical guarantee and efficient sampling

We study the problem of matrix completion in this paper. A spectral scaled Student prior is exploited to favour the underlying low-rank structure of the data matrix. Importantly, we provide a thorough theoretical investigation for our approach, while such an analysis is hard to obtain and limited in theoretical understanding of Bayesian matrix completion. More precisely, we show that our Bayesian approach enjoys a minimax-optimal oracle inequality which guarantees that our method works well under model misspeciﬁcation and under general sampling distribution. Interestingly, we also provide eﬃcient gradient-based sampling implementations for our approach by using Langevin Monte Carlo which is novel in Bayesian matrix completion. More speciﬁcally, we show that our algorithms are signiﬁcantly faster than Gibbs sampler in this problem. To illustrate the attractive features of our inference strategy, some numerical simulations are conducted and an application to image inpainting is demonstrated.
Sublanguage: A Serious Issue Affects Pretrained Models in Legal Domain

Legal English is a sublanguage that is important for everyone but not for everyone to understand. Pretrained models have become best practices among current deep learning approaches for different problems. It would be a waste or even a danger if these models were applied in practice without knowledge of the sublanguage of the law. In this paper, we raise the issue and propose a trivial solution by introducing BERTLaw a legal sublanguage pretrained model. The paper's experiments demonstrate the superior effectiveness of the method compared to the baseline pretrained model
Variational Inference for Category Recommendation in E-Commerce platforms

Category recommendation for users on an e-Commerce platform is an important task as it dictates the flow of traffic through the website. It is therefore important to surface precise and diverse category recommendations to aid the users' journey through the platform and to help them discover new groups of items. An often understated part in category recommendation is users' proclivity to repeat purchases. The structure of this temporal behavior can be harvested for better category recommendations and in this work, we attempt to harness this through variational inference. Further, to enhance the variational inference based optimization, we initialize the optimizer at better starting points through the well known Metapath2Vec algorithm. We demonstrate our results on two real-world datasets and show that our model outperforms standard baseline methods.
Human-like informative conversations: Better acknowledgements using conditional mutual information

This work aims to build a dialogue agent that can weave new factual content into conversations as naturally as humans. We draw insights from linguistic principles of conversational analysis and annotate human-human conversations from the Switchboard Dialog Act Corpus to examine humans strategies for acknowledgement, transition, detail selection and presentation. When current chatbots (explicitly provided with new factual content) introduce facts into a conversation, their generated responses do not acknowledge the prior turns. This is because models trained with two contexts - new factual content and conversational history - generate responses that are non-specific w.r. t. one of the contexts, typically the conversational history. We show that specificity w.r. t. conversational history is better captured by pointwise conditional mutual information (pcmi_h) than by the established use of pointwise mutual information (pmi). Our proposed method, Fused-PCMI, trades off pmi for pcmi_h and is preferred by humans for overall quality over the Max-PMI baseline 60% of the time. Human evaluators also judge responses with higher pcmi_h better at acknowledgement 74% of the time. The results demonstrate that systems mimicking human conversational traits (in this case acknowledgement) improve overall quality and more broadly illustrate the utility of linguistic principles in improving dialogue agents.