Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental Performance of Hydrothermal Carbonization of Four Wet Biomass Waste Streams at Industry-Relevant Scales

Hydrothermal carbonization (HTC) of green waste, food waste, organic fraction of municipal solid waste (MSW), and digestate is assessed using life cycle assessment as a potential technology to treat biowaste. Water content of the biowaste and composition of the resulting hydrochar are important parameters influencing environmental performance. Hydrochar produced from green waste performs best and second best in respectively 2 and 10 out of 15 impact categories, including climate change, mainly due to low transportation needs of the biowaste and optimized pumping efficiency for the feedstock. By contrast, hydrochar produced from the organic fraction of MSW performs best in 6 impact categories, but has high potential impacts on human health and ecosystems caused by emissions of toxic elements through ash disposal. The greatest potential for environmental optimization for the HTC technology is in the use of heat and electricity with increasing plant size, but its overall environmental performance is largely .
iPlasticity: Induced juvenile‐like plasticity in the adult brain as a mechanism of antidepressants

The network hypothesis of depression proposes that mood disorders reflect problems in information processing within particular neural networks. Antidepressants (AD), including selective serotonin reuptake inhibitors (SSRI), function by gradually improving information processing within these networks. AD have been shown to induce a state of juvenile‐like plasticity comparable to that observed during developmental critical periods: Such critical‐period‐like plasticity allows brain networks to better adapt to extrinsic and intrinsic signals. We have coined this drug‐induced state of juvenile‐like plasticity ‘iPlasticity. ’ A combination of iPlasticity induced by chronic SSRI treatment together with training, rehabilitation, or psychotherapy improves symptoms of neuropsychiatric disorders and issues underlying the developmentally or genetically malfunctioning networks. We have proposed that iPlasticity might be a critical component of AD action. We have demonstrated that iPlasticity occurs in the visual cortex, fear erasure network, extinction of aggression caused by social isolation, and spatial reversal memory in rodent models. Chronic SSRI treatment is known to promote neurogenesis and to cause dematuration of granule cells in the dentate gyrus and of interneurons, especially parvalbumin interneurons enwrapped by perineuronal nets in the prefrontal cortex, visual cortex, and amygdala. Brain‐derived neurotrophic factor (BDNF), via its receptor tropomyosin kinase receptor B, is involved in the processes of synaptic plasticity, including neurogenesis, neuronal differentiation, weight of synapses, and gene regulation of synaptic formation. BDNF can be activated by both chronic SSRI treatment and neuronal activity. Accordingly, the BDNF/tropomyosin kinase receptor B pathway is critical for iPlasticity, but further analyses will be needed to provide mechanical insight into the processes of iPlasticity.
Bulk Superconductor Levitation Devices: Advances in and Prospects for Development

Maglev train is a transportation system that uses magnetic interaction and brings many technical, economic, and environmental benefits. Here, the progress in designing and manufacturing portable vacuum cryostats containing 24 high-quality threefold seeded Yttrium Barium Copper Oxide (YBCO) bulks with up to 40 h LN2 cooled operation time is reported. Permanent magnet (PM) excitation on a magnetic guideway generates forces on the YBCO cryostats and provide train levitation forces of several tons by assembling the portable cryostats. By means of experiments and systematic improved fabrication, we describe the process of material and device scaling-up to gain industrial-near transformation and application. Current PM guideway design with the magnetic flux of 0.5 T at maximum limits the force density to 5–10 N/cm2. The conditions for further development, effective fabrication, and design-oriented progress of higher loads, great robustness, and better thermal insulation respective longer operation time are outlined.
Türkçe ses tanima sistemlerinde dil modeli boyutunun doğruluk oranina etkisi How does language model size effects speech recognition accuracy for the Turkish language

Bu calismanin hedefi, Dil Modeli (DM) uretmek icin kullanilan metin derlem buyuklugunun, Ses Tanima Sistemleri (STS) uzerindeki etkisini arastirmaktir. Calismada ayrica DM elde etmek icin yapilmasi gereken isler detayli olarak anlatilmaktadir. DM istatistiksel olarak olusturuldugundan, egitim verisinde bulunan veri miktari arttikca STS dogrulugunun artmasi beklenmektedir. Fakat Turkce gibi sondan eklemeli dillerde, kullanilan derlemin buyuklugunun hangi noktaya kadar sistemin dogruluk orani uzerinde etkin olacagi onem tasimaktadir. Bu calismada, toplanan farkli buyuklukteki metin derlemleri ile konusma tanima sisteminde Dil Model Agirligi (DMA) ve Aktif Token Sayisi (ATS) parametrelerini degistirerek yapilan deneyler yer almaktadir. Bu calisma DM boyutu buyudukce Turkce konusma tanima basariminin yukseldigini gostermektedir. Ancak, DMA ve ATS degerlerinde yapilan ayarlamalarin tanima basarimina olumlu bir etki yaptigi gozlemlenememistir. In this paper we aimed at investigating the effect of Language Model (LM) size on Speech Recognition (SR) accuracy. We also provided details of our approach for obtaining the LM for Turkish. Since LM is obtained by statistical processing of raw text, we expect that by increasing the size of available data for training the LM, SR accuracy will improve. Since this study is based on recognition of Turkish, which is a highly agglutinative language, it is important to find out the appropriate size for the training data. The minimum required data size is expected to be much higher than the data needed to train a language model for a language with low level of agglutination such as English. In the experiments we also tried to adjust the Language Model Weight (LMW) and Active Token Count (ATC) parameters of LM as these are expected to be different for a highly agglutinative language. We showed that by increasing the training data size to an appropriate level, the recognition accuracy improved on the other hand changes on LMW and ATC did not have a positive effect on Turkish speech recognition accuracy.
Offline Deduplication for Solid State Disk Using a Lightweight Hash Algorithm

Deduplication technique can expand the lifespan and capacity of flash memory-based storage devices by eliminating duplicated write operations. The deduplication techniques can be classified into two approaches, i.e., online and offline approaches. We propose an offline deduplication technique that uses a lightweight hash algorithm, whereas the previous offline technique uses a high-cost hash algorithm. Therefore, the memory space for caching hash values can be reduced, and more pages can be examined for deduplication during short idle intervals. As a result, it can provide shorter write latencies compared to the online approach, and can show low garbage collection costs compared to the previous offline deduplication technique.
Interest and Uptake of MC1R Testing for Melanoma Risk in a Diverse Primary Care Population: A Randomized Clinical Trial

Importance Germline variants in the MC1R gene are common and confer moderate melanoma risk in those with varied skin types. Approaches to precision skin cancer prevention that include genetic information may promote risk awareness and risk reduction in the general population, including Hispanics. Objective To examine prevalence of interest in and uptake of MC1R testing in the general population and examine patterns across demographic and skin cancer risk factors. Design, Setting, and Participants A randomized clinical trial examined interest in and uptake of MC1R testing among patients at University of New Mexico General Internal Medicine clinics. Study participants were randomized to either a usual-care condition (National Cancer Institute skin cancer pamphlet for diverse skin types) or an MC1R test offer. Participants were registered clinic patients (≥6 months) and English or Spanish fluent. Of the 600 participants recruited to the overall trial, the present study included those 499 participants randomized to the MC1R test offer. Interventions Participants were presented with the option to log onto the study website to read 3 educational modules presenting the rationale, benefits, and drawbacks of MC1R testing. Main Outcomes and Measures Main outcomes include website log on (yes vs no), saliva test kit request (yes vs no), and saliva test kit return for MC1R testing (yes vs no). Demographic and skin cancer risk factors were examined as potential predictors of test interest and uptake. Results Of the 499 participants (220 [44%] non-Hispanic white, 242 [48%] Hispanic, 396 [79%] female; mean [SD] age, 54 [14.3] years), 232 (46%) elected to learn about MC1R testing by logging onto the website; 204 (88%) of those who logged on decided to request testing; and 167 (82%) of those who requested testing returned the kit. The strongest predictors of website log on were race/ethnicity and education (non-Hispanic whites were more likely to log on [odds ratio for Hispanics vs non-Hispanic whites, 0.5; 95% CI, 0.3-0.7], as were more highly educated individuals [odds ratio for more than high school vs high school or less, 2.7; 95% CI, 1.7-4.3]). The strongest predictor of ordering the test was sunburn history (odds ratio, 5.4; 95% CI, 2.3-12.9 vs no sunburn history). Conclusions and Relevance There were moderately high levels of MC1R test interest and uptake in this diverse sample. Addressing potential barriers to testing may be warranted as genomic information becomes integrated into general population approaches to the precision prevention of skin cancer. Trial Registration ClinicalTrials.gov identifier: NCT03130569
Viruses, IRESs, and a universal translation initiation mechanism

Abstract Internal ribosome entry sites (IRESs) are cis-acting RNA elements capable of recruiting ribosomes and initiating translation on an internal portion of an mRNA. This is divergent from canonical eukaryotic translation initiation, where the 5’ cap is recognized by initiation factors (IFs) that recruit the ribosome to initiate translation of the encoded peptide. All known IRESs are capable of initiating translation in a cap-independent manner, and are therefore not constrained by the absence or presence of a 5’ m7G cap. In addition to being cap-independent, IRES-mediated translation often uses only a subset of IFs allowing them to function independently of canonical initiation. The ability to function independently of the canonical translation initiation pathway allows IRESs to mediate gene expression when cap-dependent translation has been inhibited. Recent reports of viral IRESs capable of initiating translation across taxonomic domains (Eukarya and Bacteria) have sparked interest in designing gene expression systems compatible with multiple organisms. The ability to drive translation independent of cellular context using a common mechanism would have a wide range of applications ranging from agriculture biotechnology to the development of antiviral drugs. Here we discuss IRES-mediated translation and critically compare the available mechanistic and structural information. A particular focus will be on IRES-meditated translation across domains of life (viral and cellular IRESs) , IRES bioengineering and the possibility of an evolutionary conserved translation initiation mechanism.
Proteomic and bioinformatic discovery of biomarkers for diabetic nephropathy

Diabetes is associated with numerous metabolic and vascular risk factors that contribute to a high rate of micro-vascular and macro-vascular disorders leading to mortality and morbidity from diabetic complications. In this case, the major cause of death in overall diabetic patients results from diabetic nephropathy (DN) or renal failure. The risk factors and mechanisms that correspond to the development of DN are not fully understood and so far, no specific and sufficient diagnostic biomarkers are currently available other than micro- or macroalbuminuria. Therefore, this review describes current and novel protein biomarkers in the context of DN as well as probable proteins biomarkers associated with pathological processes for the early stage of DN via proteomics data together with bioinformatics. In addition, the mechanisms involved in early development of diabetic vascular disorders and complications resulting from glucose induced oxidative stress will also be explored.
Distinct timing of neurogenesis of ipsilateral and contralateral retinal ganglion cells

In higher vertebrates, the circuit formed by retinal ganglion cells (RGCs) projecting ipsilaterally (iRGCs) or contralaterally (cRGCs) to the brain permits binocular vision and depth perception. iRGCs and cRGCs differ in their position within the retina and in expression of transcription, guidance and activity‐related factors. To parse whether these two populations also differ in the timing of their genesis, a feature of distinct neural subtypes and associated projections, we used newer birthdating methods and cell subtype specific markers to determine birthdate and cell cycle exit more precisely than previously. In the ventrotemporal (VT) retina, i‐ and cRGCs intermingle and neurogenesis in this zone lags behind RGC production in the rest of the retina where only cRGCs are positioned. In addition, within the VT retina, i‐ and cRGC populations are born at distinct times: neurogenesis of iRGCs surges at E13, and cRGCs arise as early as E14, not later in embryogenesis as reported. Moreover, in the ventral ciliary margin zone (CMZ), which contains progenitors that give rise to some iRGCs in ventral neural retina (Marcucci et al., 2016), cell cycle exit is slower than in other retinal regions in which progenitors give rise only to cRGCs. Further, when the cell cycle regulator Cyclin D2 is missing, cell cycle length in the CMZ is further reduced, mirroring the reduction of both i‐ and cRGCs in the Cyclin D2 mutant. These results strengthen the view that differential regulation of cell cycle dynamics at the progenitor level is associated with specific RGC fates and laterality of axonal projection.
Human Activity Recognition for Healthcare using Smartphones

The healthcare benefits associated with regular physical activity monitoring and recognition has been considered in several research studies. Solid evidence shows that regular monitoring and recognition of physical activity can potentially assist to manage and reduce the risk of many diseases such as obesity, cardiovascular and diabetes. A few studies have been carried out in order to develop effective human activity recognition system using smartphone. However, understanding the role of each sensor embedded in the smartphone for activity recognition is essential and need to be investigated. Due to the recent outstanding performance of artificial neural networks in human activity recognition, this work aims to investigate the role of gyroscope and accelerometer sensors and its combination for automatic human activity detection, analysis and recognition using artificial neural networks. The experimental result on the publicly available dataset indicates that each of the sensors can be used for human activity recognition separately. However, accelerometer sensor data performed better than gyroscope sensor data with classification accuracy of 92%. Combining accelerometer and gyroscope performed better than when used individually with an accuracy of 95%.
The Open Knowledge System for TAC KBP 2017

This paper presents the Open Knowledge System (OKS) developed for the Cold Start KB task in TAC KBP 2017. In order to complete this task, we developed seven modules, namely, the English entity discovery module, the relation extraction module, the event nugget detection module, the entity linking and clustering module, the standalone BeSt module, inference module and post processing module. Particularly, the relation extraction module combines three existing methods: RNN-based relation extraction, OpenIE and Implicit Relation Extraction.
Farm Profits and Adoption of Precision Agriculture

Precision agriculture (PA) and its suite of information technologies—such as soil and yield mapping using a global positioning system (GPS), GPS tractor guidance systems, and variable-rate input application—allow farm operators to fine-tune their production practices. Access to detailed, within-field information can decrease input costs and increase yields. USDA’s Agricultural Resource Management Survey shows that these PA technologies were used on roughly 30 to 50 percent of U.S. corn and soybean acres in 2010-12. Previous studies suggest that use of PA is associated with higher profits under certain conditions, but aggregate estimates of these gains have not been available. In this report, a treatment-effects model is developed to estimate factors associated with PA technology adoption rates and the impacts of adoption on profits. Labor and machinery used in production and certain farm characteristics, like farm size, are associated with adoption as well as with two profit measures, net returns and operating profits. The impact of these PA technologies on profits for U.S. corn producers is positive, but small.
Copper attenuates early and late biochemical alterations induced by inorganic mercury in young rats

ABSTRACT Mercury (Hg), a divalent metal, produces adverse effects predominantly in the renal and central nervous systems. The aim of this study was to determine the effectiveness of copper (Cu) in prevention of mercuric mercury (Hg2+)-mediated toxic effects as well as the role metallothioneins (MT) play in this protective mechanism in young rats. Wistar rats were treated subcutaneously with saline (Sal) or CuCl2.2H2O (Cu 2.6 mg/kg/day) from 3 to 7 days old and with saline or HgCl2 (Hg 3.7 mg/kg/day) from 8 to 12 days old. The experimental groups were (1) Sal-Sal, (2) Cu-Sal, (3) Sal-Hg, and (4) Cu-Hg. MTs and metal contents were determined at 13 and 33 days of age. Porphobilinogen synthase (PBG-synthase) activity as well as renal and hepatic parameters were measured at 33 days. At 13 day, Hg2+ exposure increased hepatic MT, Hg, zinc (Zn) and iron (Fe) levels, in kidney elevated Cu and Hg and decreased renal Fe concentrations, accompanied by elevated blood Hg levels. At 33 days, Hg2+ exposure inhibited renal PBG-synthase activity, increased serum urea levels and lowered Fe and Mg levels. Copper partially prevented the rise in blood Hg and liver Fe noted at 13 days; and completely blocked urea rise and diminished renal PBG-synthase activity inhibition at 33 days. In 13-day-old rats, Cu exposure redistributed the Hg in the body, decreasing hepatic and blood levels while increasing renal levels, accompanied by elevated renal and hepatic MT levels in Hg2+-exposed animals. These results suggest that hepatic MT might bind to hepatic and blood Hg for transport to the kidney in order to be excreted. Abbreviations: MT: metallothioneins; PBG-synthase: porphobilinogen synthase.
Effective Unsupervised Author Disambiguation with Relative Frequencies

This work addresses the problem of author name homonymy in the Web of Science. Aiming for an efficient, simple and straightforward solution, we introduce a novel probabilistic similarity measure for author name disambiguation based on feature overlap. Using the researcher-ID available for a subset of the Web of Science, we evaluate the application of this measure in the context of agglomeratively clustering author mentions. We focus on a concise evaluation that shows clearly for which problem setups and at which time during the clustering process our approach works best. In contrast to most other works in this field, we are skeptical towards the performance of author name disambiguation methods in general and compare our approach to the trivial single-cluster baseline. Our results are presented separately for each correct clustering size as we can explain that, when treating all cases together, the trivial baseline and more sophisticated approaches are hardly distinguishable in terms of evaluation results. Our model shows state-of-the-art performance for all correct clustering sizes without any discriminative training and with tuning only one convergence parameter.
Brief on Iron Compounds for Fortification of Staple Foods

Iron fortification of food is generally considered to be the best long-term strategy to increase iron intake and has been reported to contribute to iron intake among those consuming fortified foods (Samuelson et al. 2000, Osler et al. 1999, Subar et al. 1998a, 1998b, Olsson et al. 1997) in developed countries, where it has been practiced for many years. Wheat flours and breakfast cereals are the most commonly fortified foods, but maize flour (Layrisse et al. 1996) and milk (Olivares et al. 1989) are also fortified in some developing countries. Intervention trials have shown that condiments such as fish sauce, sugar, curry powder (Lynch et al. 1993), and salt (Nadiger et al. 1980) can be effectively fortified with iron and improve iron status.
Multi-hop Inference for Sentence-level TextGraphs: How Challenging is Meaningfully Combining Information for Science Question Answering?

Question Answering for complex questions is often modelled as a graph construction or traversal task, where a solver must build or traverse a graph of facts that answer and explain a given question. This “multi-hop” inference has been shown to be extremely challenging, with few models able to aggregate more than two facts before being overwhelmed by “semantic drift”, or the tendency for long chains of facts to quickly drift off topic. This is a major barrier to current inference models, as even elementary science questions require an average of 4 to 6 facts to answer and explain. In this work we empirically characterize the difficulty of building or traversing a graph of sentences connected by lexical overlap, by evaluating chance sentence aggregation quality through 9,784 manually-annotated judgements across knowledge graphs built from three free-text corpora (including study guides and Simple Wikipedia). We demonstrate semantic drift tends to be high and aggregation quality low, at between 0.04 and 3, and highlight scenarios that maximize the likelihood of meaningfully combining information.
A 5.8 GHz Digitally Controlled CMOS Receiver With a Wide Dynamic Range for Chinese ETC System

This brief presents a 5.8 GHz digitally controlled dedicated short range communications (DSRC) receiver for Chinese electronic toll collection systems. All RF, IF blocks and digital baseband for on-chip automatic gain control, are integrated on an RF system-on-chip (RF-SoC). The proposed digitally controlled low noise amplifier (LNA) and mixer circuits are elaborated. The test chip was realized in a 0.13-<inline-formula> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula> CMOS technology. The RF blocks in receiver occupy a chip area of 0.75 mm<sup>2</sup>. The receiver blocks consume 22 mA under a 1.5-V supply voltage. Measurement results show that the bit error rate maintains better than 10<sup>−6</sup>, while the input power level varies from −75 dBm to −8 dBm. This design results in a receiver sensitivity improvement of at least 25%, and a dynamic range enhancement of at least 12%.
Establishing unconsidered factors that anchor the thrive of micro and small enterprises in developing and under developed economy revised edition

The focus of this paper is to microscopically, identify and analyze unconsidered factors in developing and underdeveloped countries that continue to impinge the successful expansionist mission of micro and small scale Enterprise. It also seek to further produce an in-depth analysis of identified causes that promote sustenance performance of micro and small enterprise, lacking Entrepreneurial character to expand in developing and underdeveloped economy