Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic Mapping Study on Use of Pre-Trained Open Machine Learning Models

Accurate understanding of pre-trained open source machine learning models, and their frameworks, and datasets use can helpsoftwareengineerssimplify,reducecosts,andimprovethequalityofapplicationdevelopmenttodifferentdomains. This paper investigates how pre-trained Open Machine Learning (ML) models, and their frameworks, and datasets are shared and used in different domains. A systematic mapping study is used to identify published studies. Statistical and qualitative results are formed for 499 studies which provide sufficient information regarding the use of open source pre-trained models, frameworks, and datasets. Based on a relatively large sample, the reviewed 499 studies provide a listing of Open ML models, frameworks, and datasets used in research as well as their relative popularity. The selected studies consisted of a large number of different domains, which saw benefits ranging from minor decline to moderate improvement when compared to thepreviouslyusedstateoftheartmachinelearningmethods. MostofthemodelsinstudieswereusedundertheTensorFlow framework with ImageNet as the dataset. The majority of studies were made in laboratory environments. Pre-trained Open ML models show positive promise for improvement in machine learning. Additional diversity of available open source models pre-trained with different datasets would improve this effect. More comparable studies are needed, especially from the industry, that use and apply open source machine learning, which report their context, methodology, and performance comprehensively.
Improving Disaster Response by Combining Automated Text Information Extraction from Images and Text on Social Media

During disasters, social media can serve as a valuable source of real-time information about the impacts on people and infrastructure. However, due to the lack of geographical information in most social media posts, this information is often underutilized by ﬁrst responders. Previous research has attempted to estimate the location of individual social media posts using text and image analysis, but limitations still exist in ﬁne-grained disaster area mapping. To address this issue, this paper analyses the performance of combining text from social media post with textual information from the images on improving the geolocation of social media information during a disaster.
Efficient Interdomain Multicast Delivery in Disruption Tolerant Networks

Mobile nodes in some challenging network scenarios suffer from intermittent connectivity and frequent partitions e.g. battlefield and disaster recovery scenarios. Disruption Tolerant Network (DTN) technologies are designed to enable nodes in such environments to communicate with one another. In the past, we have proposed two intradomain multicast routing schemes, namely the context-aware multicast routing (CAMR) and Encounter-based Multicast Routing (EBMR) schemes. In this paper, we consider the problem of routing multicast messages across different domains. We present a ferry based interdomain multicast delivery scheme where a ferry is used to deliver multicast messages across groups that are partitioned and a variant of the encounter-based multicast routing scheme is used as the intradomain routing scheme for intradomain delivery. We then present simulation results using different group mobility models to illustrate the usefulness of the scheme we design. Our results indicate that the scheme we design can achieve high delivery ratio with reasonable data efficiency. Our results also indicate that the delivery ratio seen using a more realistic VANET model is slightly worse than that seen using the RPGM model.
Evolution of a small phage protein confers resistance to antiphage defense in 2 Enterococcus faecalis 3

23 The prevalence of multidrug resistant (MDR) bacterial infections continues to rise as the 24 development of new antibiotics needed to combat these infections remains stagnant. MDR 25 enterococci, which are a common cause of hospital-acquired infections, are emerging as one of 26 the major contributors to this crisis. A potential therapeutic approach for combating MDR 27 enterococci is bacteriophage (phage) therapy, which entails the use of lytic viruses to infect and 28 kill pathogenic bacteria. While phages that lyse some strains of MDR enterococci have been 29 identified, other strains display high levels of phage resistance and the mechanisms underlying 30 this resistance are unknown. Here, we use a CRISPR interference (CRISPRi) screen to identify 31 a genetic locus found on a mobilizable plasmid from vancomycin-resistant Enterococcus 32 faecalis involved in phage resistance. This locus encodes a putative serine recombinase 33 followed by a Type IV restriction enzyme (TIV-RE) and we show that this enzyme is sufficient to 34 restrict the replication of the lytic phage in E. faecalis . We further find that phages can evolve to 35 overcome restriction by acquiring a missense mutation in a novel TIV-RE inhibitor protein 36 encoded by many enterococcal phages. We show that this inhibitor, which we have named anti-37 restriction-factor A ( arfA ), directly binds to and inactivates diverse TIV-REs. Overall, our findings 38 significantly advance our understanding of phage defense in drug-resistant E. faecalis and 39 provide mechanistic insight into how phages can evolve to overcome antiphage defense 40 systems. 41 42 43 44 45 46
pollut-Changes in Inorganic Chemical Species in Fog Water over Delhi

Heavy fogs occur during the winter period over the part of northern India and impact aviation, public transport, the economy, public life, etc. During winter, fog water (FW) and non-monsoonal rainwater (NMRW) samples were collected in Delhi, which is a highly polluted and populated megacity in northern India. The collected FW and NMRW samples were analyzed for their inorganic chemical constituents (F - , Cl - , SO 42 - , NO 3 - , NH 4 + , Na + , K + , Ca 2 + , and Mg 2 + ). The volume-weighted mean (VWM) pH, conductivity, and total dissolved solids (TDS) of FW were 6.89, 206 μS cm - 1 , and 107 mg L - 1 , respectively, indicating the dominance of alkaline species. The total measured ionic constituents (TMIC) in FW and NMRW were 5,738 and 814 μeq L - 1 , respectively, indicating highly concentrated FW in Delhi. The TMIC in FW were factors of 16 and 7 times more concentrated than MRW and NMRW samples, respectively. The concentrations of inorganic acidic species (SO 42 - and NO 3 - ) in FW were much higher than in monsoon rainwater (MRW: 3 and 5 times) and NMRW (8 and 12 times), respectively. Also, the concentrations of SO 42 - and NO 3 in NMRW were approximately double compared to MRW indicating higher acidic species concentrations during the winter season over Delhi region. Significant decadal growth in the mean concentrations of ionic species in FW (SO 42 - - ~ 9 times; NH 4 + - double) were observed between 1985 and 2010. However, the nitrate decreased by ~ 28%. The higher SO 42 - is likely from heavy-duty vehicles that burn sulfur-containing fuel. The anions in FW, MRW, and NMRW contributed 20, 42, and 43%. However, the cation contributions were 80, 58, and 57%, respectively. The anion contributions were lower in FW than MRW and NMRW indicating the weak formation of acidic species in fog water. The observed alkalinity suggests that it is unlikely for acid precipitation to be present in this region.
Continuing 137 Cs release to the sea from the Fukushima Dai-ichi Nuclear Power Plant through 2012

The rate of cesium-137 ( 137 Cs) release to the sea from the Fukushima Dai-ichi Nuclear Power Plant for the period until September 2012 was estimated. Publicly released data on 137 Cs radioactivity in seawater near the power plant by Tokyo Electric Power Company strongly suggest a continuing release of radionuclides to the sea. The plant has an artificial harbour facility, and the exchange rate of harbour water with surrounding seawater was estimated by the decrease in radioactivity immediately after an intense radioactive water release. The estimated exchange rate of water in the harbour was 0.44 d −1 during the period from 6 to 19 April. The 137 Cs radioactivity in the harbour water was substantially higher than that of seawater outside and remained relatively stable after June 2011. A quasi-steady state was assumed with continuous water exchange, and the average release rate of 137 Cs was estimated to be 93 GBq d −1 in summer 2011 and 8.1 GBq d −1 in summer 2012.
Global variations of surface ocean productivity in low and mid latitudes: Influence on CO2 reservoirs of the deep ocean and atmosphere during the last 21,000 years

Based on detailed reconstructions of global distribution patterns, both paleoproductivity and the benthic δ13C record of CO2, which is dissolved in the deep ocean, strongly differed between the Last Glacial Maximum and the Holocene. With the onset of Termination I about 15,000 years ago, the new (export) production of low- and mid-latitude upwelling cells started to decline by more than 2-4 Gt carbon/year. This reduction is regarded as a main factor leading to both the simultaneous rise in atmospheric CO2 as recorded in ice cores and, with a slight delay of more than 1000 years, to a large-scale gradual CO2 depletion of the deep ocean by about 650 Gt C. This estimate is based on an average increase in benthic δ13C by 0.4–0.5‰. The decrease in new production also matches a clear 13C depletion of organic matter, possibly recording an end of extreme nutrient utilization in upwelling cells. As shown by Sarnthein et al., [1987], the productivity reversal appears to be triggered by a rapid reduction in the strength of meridional trades, which in turn was linked via a shrinking extent of sea ice to a massive increase in high-latitude insolation, i.e., to orbital forcing as primary cause.
Mathematical model for predicting soil erosion by flowing water in ungauged watersheds.

A model was developed for estimating soil erosion by flowing water in ungauged watersheds from four parameters: slope; annual rainfall; clay content; and vegetation cover. The mathematical model is: soil erosion (t ha) = 41.73 + 0.181 × slope (%) + 0.046 × rainfall (cm) – 0.387 × clay (%) – 8.125 × vegetation cover factor. The vegetation cover was ranked on a scale of 1 to 5, 1 being bare soil surface, and 5 the extremely dense forests with trees, bushes and grasses. The model was applied to the data obtained from gauged watersheds during subsequent years for validity and was found quite effective in estimating soil erosion by water. However, further investigations are required to refine the model. Furthermore, because the gauged watersheds comprise only a minute fraction of the total ungauged area of the region, estimating soil erosion estimation necessitates spatial extrapolation on a spatial and temporal basis.
Comments on “Current GCMs' Unrealistic Negative Feedback in the Arctic”

AbstractIn contrast to prior studies showing a positive lapse-rate feedback associated with the Arctic inversion, Boe et al. reported that strong present-day Arctic temperature inversions are associated with stronger negative longwave feedbacks and thus reduced Arctic amplification in the model ensemble from phase 3 of the Coupled Model Intercomparison Project (CMIP3). A permutation test reveals that the relation between longwave feedbacks and inversion strength is an artifact of statistical self-correlation and that shortwave feedbacks have a stronger correlation with intermodel spread. The present comment concludes that the conventional understanding of a positive lapse-rate feedback associated with the Arctic inversion is consistent with the CMIP3 model ensemble.
Analysis of a two-state Markov ﬂuid model with 2 buffers

Single buffer Markov ﬂuid models are well understood in the literature, but the extension of those results for multiple buffers is still an open research problem. In this paper we consider one of the simplest Markov ﬂuid models (MFM) with 2 buffers of inﬁnite capacity, where the ﬂuid rates ensure that the ﬂuid level of buffer 1 is never larger than ﬂuid level of buffer 2. In spite of these restrictions, the stationary analysis is non straightforward with the available analysis tools. We provide an analysis approach based on the embedded time points at the busy-idle cycles of buffer 1.
A REVIEW ON ATTENTION DEFICIENT HYPERACTIVITY DISORDER

: Attention Deficiency hyperactivity complaint( ADHD) is a neurodevelopmental complaint in which cases present inattention, hyperactivity, and impulsivity. The etiology of this condition is different, including environmental factors and the presence of variants of some genes. Still, a great diversity exists among cases regarding the presence of these ADHD-associated factors. also, there are variations in the reported neurophysiological supplements of ADHD. ADHD is constantly treated pharmacologically, producing an improvement in symptomatology , albeit there are cases who are refractory to the main pharmacological treatments or present side goods to these drugs, pressing the significance of developing other remedial options. Differentnon-pharmacological treatments are in this review addressed, chancing different results regarding effectiveness. Altogether, ADHD is associated with different etiologies, all of them producing changes in brain development, leading to the characteristic symptomatology of this condition. Given the eclectic etiology of ADHD, discussion is presented about the convenience of personalizing ADHD treatment, whether pharmacological ornon-pharmacological, to reach an optimum effect in the maturity of cases. Approaches to personalizing both pharmacological remedy and neurofeedback are presented.
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching

In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compared to traditional image filtering techniques. This paper aimed to utilize a specific CNN architecture known as AlexNet for the fingerprint-matching task. Using such an architecture, this study has extracted the significant features of the fingerprint image, generated a key based on such a biometric feature of the image, and stored it in a reference database. Then, using Cosine similarity and Hamming Distance measures, the testing fingerprints have been matched with a reference. Using the FVC2002 database, the proposed method showed a False Acceptance Rate (FAR) of 2.09% and a False Rejection Rate (FRR) of 2.81%. Comparing these results against other studies that utilized traditional approaches such as the Fuzzy Vault has demonstrated the efficacy of CNN in terms of fingerprint matching. It is also emphasizing the usefulness of using Cosine similarity and Hamming Distance in terms of matching.
Weathering the Storm: Options for Framing Adaptation and Development

The report analyzes the objectives of initiatives and the strategies utilized in implementation to characterize some of the ways that adaptation and development overlap. A continuum of activities from “pure” development to “pure” climate change is proposed as a conceptual framework to understand when different “development” activities may play an “adaptation” function. Recommendations address governance challenges, funding implications, and next steps in analysis and policy development.
GRAIN SIZE INFORMATION IN DIFFERENT EVOLUTION PERIODS OF XINYANGGANG TIDAL FLAT IN JIANGSU PROVINCE

Six sediment cores were collected in Xinyanggang,Jiangsu Province,in August 2007.Sediment spatial distribution characteristics were studied by analyzing grain size.Grain size parameters and typical frequency distribution curves combining with the changes in color of different core sediments were analyzed for extraction of grain size information in different evolution periods.Standard deviation of grain size components was used for environmental sensitivity analysis to understand the impact of dynamic characteristics on distribution of tidal flat sediments.Deposition rates were estimated in accordance with the evolution periods of tidal flat.The results showed that,core sediment of silt Flat gave grain size evolution information from silt flat to Spartina angilica flat,and then to silt flat again.However,core sediments of Spartina alterniflora flat,Suaeda salsa flat and transitional Spartina alterniflora and Suaeda salsa flats recorded grain size evolution information of Spartina angilica flat-Spartina alterniflora flat,Suaeda salsa flat-Spartina angilica flat-Suaeda salsa flat,Suaeda salsa flat-Spartina angilica flat-transitional Suaeda salsa and Spartina alterniflora flats,respectively.The difference and variation of hydrodynamics in different positions of tidal flat led to the coarse-fine variety of sediments horizontally from silt flat-Spartina alterniflora flat-Suaeda salsa flat gradually,and resulted in the fact that reed flat became an independent environmental system which was very stable.And vegetation covers impelled this process,which was evidently reflected in grain size variation of surface sediments.Deposition rates of silt flat,Spartina alterniflora flat,transitional Spartina alterniflora and Suaeda salsa flats and Suaeda salsa flat were 2.34 cm/a,≥3.09 cm/a,2.45 cm/a and 2.09 cm/a respectively.
Artiﬁcial-Intelligence-Assisted Activities of Daily Living Recognition for Elderly in Smart Home

: Activity Recognition (AR) is a method to identify a certain activity from the set of actions. It is commonly used to recognize a set of Activities of Daily Living (ADLs), which are performed by the elderly in a smart home environment. AR can be beneﬁcial for monitoring the elder’s health condition, where the information can be further shared with the family members, caretakers, or doctors. Due to the unpredictable behaviors of an elderly person, performance of ADLs can vary in day-to-day life. Each activity may perform differently, which can affect the sequence of the sensor’s raw data. Due to this issue, recognizing ADLs from the sensor’s raw data remains a challenge. In this paper, we proposed an Activity Recognition for the prediction of the Activities of Daily Living using Artiﬁcial Intelligence approach. Data acquisition techniques and modiﬁed Naive Bayes supervised learning algorithm are used to design the prediction model for ADL. Our experiment results establish that the proposed method can achieve high accuracy in comparison to other well-established supervised learning algorithms.
Use of Early Juvenile Zebrafish

Reliable and cost-effective early-life stage (ELS) bioassays incorporating practical experimentation without compromising scientific relevance are crucial in chemical risk assessment. This study investigated the use of 20 days-post-fertilization life stage ( 20dpfZF ) of zebrafish Danio rerio to screen environmental chemicals known to be estrogenic in adult fish. Firstly, studies with key genes in steroidogenesis were conducted; the brain isoform of aromatase gene ( cyp19a1b ) being the most prominently expressed biomarker. Regulation of mRNA levels of molecular biomarkers, vitellogenin 1 gene ( vtg1) and cyp19a1b were selected to assess the endocrine modulation by xenoestrogens, 17α-ethinylestradiol (EE2), 4-n -nonylphenol (NP), 4-t -octylphenol (OP) and bisphenol A (BPA). Groups of 20dpfZF (n=15) as three replicates were exposed to chemicals over a five-day period in aerated static setups. Exposure of 20dpfZF to sediment spiked with EE2 (nominal 3µg g -1 dw) was also conducted to assess the sensitivity of this life-stage to sediment with estrogenic potency. Whole body homogenates of exposed juveniles showed the estrogenic potential of chemicals in the order: EE2 > OP > BPA > NP. Higher relative expression of cyp19a1b was noticed at lower ambient concentrations of EE2, although vtg1 showed more pronounced expression to it. The 20dpfZF responded in a dose-related way to sediment spiked with EE2, expanding its use as a general aquatic animal model. The suitability of 20dpfZF as an in vivo model, along with stable expression of reference genes was established. In addition to consistent expression pattern of key target genes on xenoestrogenicity, it serves as a practical screening model for the risk assessment of environmental chemicals and samples with estrogenic potential.
eCommons@AKU eCommons

Objective: To determine the frequency of persistent pain in patients after breast cancer surgery, and to assess the distribution and characteristics of pain in such patients. Method: The prospective observational single cohort study was conducted at the Department of Anaesthesiology and in the Breast Clinic of the Department of Surgery, Aga Khan University Hospital, Karachi, from August 2016 to January 2017, and comprised adult female patients with biopsy-proven carcinoma of breast who were scheduled for elective definitive breast cancer surgery. The patients were followed up for up to three months post-surgery and those with persistent pain were followed up for six months post-operation. Data was analysed using SPSS 19. Results: Of the 120 patients, 26(21.7%) developed persistent post-surgical pain for up to three months, while in 17(14.2%) patients, the pain continued for up to six months after the operation. Among those with persistent post-surgical pain, 11(42.3%) had burning pain, 10(38.5%) had throbbing pain, 3(11.5%) had numbness and 2(7.7%)had mixed character of pain. Also, 11(42.3%)patients developed pain at more than one site including axilla, chest wall, upper arm and surgical scar area, and the site of pain in majority patients 15(57.7%) was axilla. Conclusion: The incidence of persistent pain following breast cancer surgery was found to be 21.7%.
Visualization of the Phylogenetic Content of Five Genomes using Visualization of the Phylogenetic Content of Five Genomes using Dekapentagonal Maps Dekapentagonal Maps

Visualization of the phylogenetic content of five genomes using dekapentagonal maps The methods presented here summarize phylogenetic relationships of genomes in visually appealing and informative figures. Dekapentag-onal maps depict phylogenetic information for orthologous genes present in five genomes, and provide a pre-screen for putatively horizontally transferred genes. If the majority of individual gene phylogenies are unresolved, bipartition histograms provide a means of uncovering and analyzing the plurality consensus. Analyses of genomes representing five photosynthetic bacterial phyla and of the prokaryotic contributions to the eukaryotic cell illustrate the utility of the methods. Abstract The methods presented here summarize phylogenetic relationships of genomes in visually appealing and informative figures. Dekapentagonal maps depict phylogenetic information for orthologous genes present in five genomes, and provide a pre-screen for putatively horizontally transferred genes. If the majority of individual gene phylogenies are unresolved, bipartition histograms provide a means of uncovering and analyzing the plurality consensus. Analyses of genomes representing five photosynthetic bacterial phyla and of the prokaryotic contributions to the eukaryotic cell illustrate the utility of the methods.