Miracle-dz/UniFAR-FTUs huggingface dataset:
Work Disability Among Injured Workers with Chronic Upper Extremity Disorders: Measurement and Determinants

Work disability represents an important source of the burden for individuals recovering from a work-related upper-extremity disorder (WRUED). Historically, a small subset of injured workers has shown to experience a prolonged recovery course characterized by poor health and work outcomes, which are associated with high workers’ compensation costs. Beyond achieving an initial return-to-work, the sustainability of work (i.e. staying at work) and health-related work limitations (i.e. “on-the-job” problems) are increasingly recognized as relevant concerns in this population. In this thesis, three quantitative studies were conducted to contribute insights to the measurement and determinants of work disability associated with WRUEDs, using survey data gathered from injured workers attending a Workplace Safety & Insurance Board Upper-Limb Specialty Clinic in Ontario. Specifically, these studies investigated 1) the factorial validity of the Work Limitations Questionnaire (WLQ-25), 2) the predictive ability of the Upper-Limb Work Instability Scale (UL-WIS) for subsequent transitioning out of work (i.e. poor sustainability of work), and 3) the relationship between the work environment and health-related work limitations, among
Recent advancements in the functionality of the components from goat milk and its products

© Abstract: The purpose of this review is to present inclusive information regarding the recent advancements in the functionality of the components from goat milk and its products. In view of the expected revenues from global goat milk and products touching USD 15 billion in 2024, there is an urgent need to capitalize on designed fermented dairy products from goats with increased participation of bioactive ingredients in goat milk which in turn lead to excellent biological effects in terms of higher therapeutic and nutritional value. Functional properties enhanced the development of innovative goat dairy products and increased the consumer demand. Goat milk as a potential functional food which is an emerging area for the development of goat milk products by using prebiotics and probiotics. A detailed list of dairy goat milk processors and products commercially available worldwide has also been discussed. The paper suggests that in future the Goat Breeder’s Associations need to be established in India on the pattern of US/International Associations to improve the quantity and quality of goat milk for in-depth studies on functionality of the components from goat milk and its products related to medicinal properties of goat milk as therapeutic health food (nutraceutical) and fermented milk beverages/products made with probiotic
“Running the Numbers”: Modes of Microcelebrity Labor in Queer Women’s Self-Representation on Instagram and Vine

Microcelebrity, as a set of practices contributing to personalized self-branding, has become an increasingly prominent component of self-representation on social media platforms. While “influencers” who have built lucrative followings through microcelebrity give the appearance of having fun without much exertion, recent studies have uncovered multiple forms of labor involved in their practices of cultural production. In addition, scholars analyzing lesbian, gay, bisexual, transgender, and queer (LGBTQ) influencers highlight a tension between labor in service of self-commodification and the representation of sexual minorities. This article examines the microcelebrity labor of everyday queer women who aim to increase their social and economic capital by interweaving personal self-representations with entrepreneurial endeavors on Instagram and Vine. Through a close analysis of these platforms’ markets, governance, and infrastructures alongside interviews with queer female users of each platform, attention is given to both platform influences and participants’ experiences of promoting their jobs, side-gigs, hobbies, or passions alongside the rest of their lives. Findings identify three modes of labor specific to participants’ efforts to build a following: (1) intimate affective labor expended in sharing and managing personal disclosures; (2) developmental aesthetic labor as the acquisition and practice of technical skills and bodily displays to achieve a desired appearance or performance; (3) aspiring relational labor in attempts to forge relationships with established influencers or celebrities. Sexual identity was pivotal across these modes of labor, as it enhanced intimacy with followers, provided a niche audience for self-branding, conveyed authenticity through self-revelation, and established a common ground for forging relationships.
GDPR: Is your consent valid?

The General Data Protection Regulation (GDPR) 2018 imposes much greater demands on companies to address the rights of individuals who provide data, that is, Data Subjects. The new law requires a much more transparent approach to gaining consent to process personal data. However, few obvious changes to how consent is gained from Data Subjects to comply with this. Many companies are running the risk of non-compliance with the law if they fail to address how data are obtained and the lack of true consent which Data Subjects currently give to their data being processed. Consent is a complex philosophical principle which relies on the person giving the consent being in full possession of the facts, this article explores the philosophical background of consent and examines the circumstances which were the point of departure for the debate on consent and attempts to develop an understanding of it in the context of the growing influence of information systems and the data-driven economy. The GDPR has gone further than any other regulation or law to date in developing an understanding of consent to address personal data and privacy concerns.
The composition characteristics of arbuscular mycorrhizal fungal communities associated with barley in saline-alkaline soils in Central Anatolia

ABSTRACT Central Anatolia, which suffers from salinity, alkalinity, and drought stresses, is one of the most important cultivation regions of barley (Hordeum vulgare) in Turkey. Arbuscular mycorrhizal fungi (AMF) could promote barley production under several stresses; however, only a little information is available for AMF community composition in Turkish arable soils. In this study, barley root samples were collected from eight sites in the Central Anatolian region during the growing season (GS: April) and the harvest season (HS: July) in 2012, and the composition of AMF communities were elucidated based on the partial sequence of the AMF 18S rRNA gene using high-throughput sequencing technology. As a result, barley-AMF symbioses in this region were highly dominated by Glomeraceae (71.8% in GS and 59.2% in HS), followed by Claroideoglomeraceae (10.3% in GS and 15.9% in HS), Gigasporaceae (9.1% in GS and 13.1% in HS), and Acaulosporaceae (5.8% in GS and 7.7% in HS). Compared to Glomeraceae and Claroideoglomeraceae families, communities of Acaulosporaceae, Diversisporaceae, Paraglomeraceae, and Gigasporaceae consisted of fewer AMF species. The AMF evenness significantly increased from GS to HS. The most dominant AMF sequence, VTX00248 in the MaarjAM database, was closely related to Rhizophagus, which occupied 25.8% and 14.7% of the total AMF sequences in GS and HS, respectively. The relative abundance of AMF related to Rhizophagus tended to be reduced in HS, suggesting that the species could form mycorrhiza in the early stages of barley growth in this region. On the other hand, the relative abundance of Claroideoglomeraceae and Scutellosporaceae tended to increase in HS. Soil CaCO3 content significantly influenced AMF community compositions in GS, while soil pH and EC showed no significant impact on AMF community compositions. Based on discriminant analysis, 11 VTXs (related Acaulospora, Claroideoglomus, Funneliformis, Gigaspora, and Glomus) showed higher abundance in the barley roots grown in the soil with relatively high CaCO3 content, suggesting that these sequences might be adapted to such an environment.
Clinical research Surgical treatment of thoracic outlet syndrome: immediate and mid-term results

Introduction: We report the results from a consecutive series of patients treated by scalenectomy or cervical rib resection for clearly symptomatic or paucisymptomatic thoracic outlet syndrome (TOS) over a 6-year period. Material and methods: From September 1999 to August 2005, 14 surgical decompressions were performed in 12 patients with unremitting signs and symptoms of nerve or vascular compression at the thoracic outlet. The symptoms of TOS were due to involvement of the brachial plexus in 8 cases (57.1%). A sign of vascular obstruction could be detected in 10 cases (71.4%): in 6 cases (42.8%) the presentation was predominantly arterial (arm claudication, coldness, Raynaud’s phenomenon and distal embolisation) and in 4 cases (28.5%) was related to vein compression with congestion and swelling of the affected arm or vein thrombosis. Two patients presented as emergencies with critical upper limb ischaemia or distal vessel embolisation. Results: The median follow-up period was 28.2 months (range 8-78 months). Results were evaluated in terms of technical success, lack of complications (temporary or permanent plexus injury, temporary or permanent phrenic palsy), relief of symptoms. Outcome data were divided into immediate/perioperative and mid-term results. Perioperative results: There was no operative mortality. Technical success was achieved in all patients in excision of the fibrous band with scalenectomy and in cervical rib excision. Mid-term results: In 4 patients with venous symptoms complete relief was achieved in 75%. In all patients who experienced arterial complications we registered complete relief. In patients with neurological presentation we detected complete relief in 5 (62.5%), relief of some symptoms in 2 (25%) and no improvement in 1 (12.5%). Conclusions: Scalenectomy performed by a standard supraclavicular approach seems to allow relief in the majority of patients with symptoms of neurological, arterial or venous compression at the thoracic outlet. Nevertheless, we emphasize the importance of an objective method of evaluation and the necessity of a prolonged follow-up.
A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning

Classical Conditioning is a fundamental learning mechanism where the Ventral Striatum is generally thought to be the source of inhibition to Ventral Tegmental Area (VTA) Dopamine neurons when a reward is expected. However, recent evidences point to a new candidate in VTA GABA encoding expectation for computing the reward prediction error in the VTA. In this system-level computational model, the VTA GABA signal is hypothesised to be a combination of magnitude and timing computed in the Peduncolopontine and Ventral Striatum respectively. This dissociation enables the model to explain recent results wherein Ventral Striatum lesions affected the temporal expectation of the reward but the magnitude of the reward was intact. This model also exhibits other features in classical conditioning namely, progressively decreasing firing for early rewards closer to the actual reward, twin peaks of VTA dopamine during training and cancellation of US dopamine after training.
A brief overview of detectors used for terahertz imaging systems

This paper presents a short review on terahertz imaging systems based on several types of technology used in the terahertz detection schemes. Some commercial products from ThruVision Systems Limited Company have utilized GaAs Schottky diode detector at 0.25 THz to produce passive terahertz images for public and homeland security. On the other hand, TeraSense Group Incorporated Company has developed and invented a ground-breaking technology which employs sensor consisting of a matrix of plasmonic semiconductor detectors in their latest products to generate terahertz images in the 0.1 – 1.0 THz frequency range. Recently, the utilization of two-terminal unipolar nanodiodes, known as the self-switching diodes (SSDs), as terahertz detectors has shown promising results. The planar structure of SSD not only enables the device to operate at high frequencies due to low intrinsic parasitic capacitance, but also allows the realization of the device using only a single lithography step. This makes the fabrication process of SSDs faster, more simple, and at lower cost when compared to other electronic devices such as Schottky diodes. The development and recent achievement of SSDs as terahertz detectors are also presented in this paper.This paper presents a short review on terahertz imaging systems based on several types of technology used in the terahertz detection schemes. Some commercial products from ThruVision Systems Limited Company have utilized GaAs Schottky diode detector at 0.25 THz to produce passive terahertz images for public and homeland security. On the other hand, TeraSense Group Incorporated Company has developed and invented a ground-breaking technology which employs sensor consisting of a matrix of plasmonic semiconductor detectors in their latest products to generate terahertz images in the 0.1 – 1.0 THz frequency range. Recently, the utilization of two-terminal unipolar nanodiodes, known as the self-switching diodes (SSDs), as terahertz detectors has shown promising results. The planar structure of SSD not only enables the device to operate at high frequencies due to low intrinsic parasitic capacitance, but also allows the realization of the device using only a single lithography step. This makes the fabrication pro.
Relaxed Multi-Instant Fuzzy State Estimation Design of Discrete-Time Nonlinear Systems and its Application: A Deep Division Approach

The problem of relaxed state estimation design of multi-instant fuzzy switching observer for discrete-time nonlinear systems is studied by proposing a deep division approach. Firstly,both the enhancement factor and the attenuation factor for each normalized fuzzy weighting function are for the first time introduced synchronously in order to derive much finer subdivisions of the whole spanning space constituted by all the normalized fuzzy weighting functions. Consequently, a more advanced ranking-based switching mechanism can be proposed over the previous results. Secondly, a new multi-instant fuzzy switching observer with different gain matrices for each finer subdivision is designed with the help of the given switching mechanism and thus much more freedom can be brought for reducing the conservatism of existing designs of fuzzy observers. More importantly, it is worth noting that the calculation of all the involved gain matrices belongs to a feasible off-line process. Finally, two simulation examples including tunnel diode circuits are provided to validate the progressiveness of the proposed deep division approach.
DETECTION AND INFERENCE IN GRAVITATIONAL WAVE ASTRONOMY

We explore the detection and astrophysical modeling of gravitational waves detected by the Advanced Laser Interferometer Gravitational wave Observatory (LIGO) and Virgo. We discuss the techniques used in the PyCBC search pipeline to discover the first gravitational wave detection GW150914, and estimate the statistical significance of GW150914, and the marginal trigger LVT151012. During Advanced LIGO’s first observing run there were no detections of mergers from binary neutron star and neutron star-black hole binaries. We use Bayesian inference to place upper limits on the rate of coalescence of these binaries. We use developments made in the PyCBC search pipeline during Advanced LIGO and Virgo’s second observing run to re-analyze Advanced LIGO’s first observing run and re-estimate the statistical significance of LVT151012. We present sufficient evidence to claim LVT151012 as a gravitational wave event. In Advanced LIGO and Virgo’s 2nd observing run a gravitational wave due to the merger of two binary neutron stars, known as GW170817, was discovered. We develop tools for Bayesian hypothesis testing so that we can investigate the interior dynamics of neutron stars using the GW170817 signal. Finally, we use Bayesian parameter estimation from PyCBC with tools of Bayesian hypothesis testing to investigate the presence of nonlinear tidal dynamics from a pressure – gravity mode instability in GW170817. We find that significant waveform degeneracies allow the effect of nonlinear tides to be compatible with the data at the level of nonsignificance (Bayes factor of unity). We also investigate further constraints on these nonlinear tides. DETECTION AND INFERENCE IN GRAVITATIONAL WAVE ASTRONOMY
Multi-site Programming Offered to Promote Resilience in Military Veterans: A Process Evaluation of the Just Roll With It Bootcamps

Background and Purpose: Military and veteran suicide rates exceed those found in the general population. Veterans often reject patient identities, creating barriers to care for mental health within the clinical sector and a mandate for prevention programs. The purpose of this study was to offer a postintervention process evaluation of one peer-led resilience program offered to military veterans of Iraq and Afghanistan at three sites in 2013. Methods: Secondary analysis of survey data collected involved mixed-methods analysis of open and closed-ended questions. In total, the research team reviewed 52 electronic survey responses; participant response rate was 48.1%. Results: Descriptive data analysis found that all participants rated Just Roll With It Bootcamp content as “somewhat useful” (17.9%) or “very useful” (82.1%). Qualitative analysis of open-ended questions found that content was perceived as valuable by participants. Emergent themes included: health practices, social support, and participant quality of life or satisfaction. Comments also informed four subthemes which included: meditation/mindfulness, nutrition, physical practice, and the seminars’ physical environment. Conclusion: Culturally-informed prevention programs that emphasize social support, physical movement, and peer-leadership have a vital role to play in working to prevent suicide by promoting quality of life for veterans.
What Influences Adoption of Green Award Criteria in a Public Contract? An Empirical Analysis of 2018 European Public Procurement Contract Award Notices

Green public procurement (GPP) is a policy tool aiming to achieve environmental protection and resource reservation via public procurement. After decades of adaptation, what promotes and hinders its uptake in public contracting remains difficult to discern. This research explores factors that influence the adoption of green award criteria, covering features of procurement procedures, purchasers, tenderers, and the business sectors through empirical analysis of Probit regression combined with a fixed term method. The data is contract award notices (CAN) from 33 countries in Europe in 2018. Our findings suggest that framework agreements, the medical products sector, the health and social services sector, and the business services sector are negatively correlated with whether a contract is green. On the other hand, the contract value, Government Procurement Agreement (GPA)coverage, joint procurement, competitive dialogue, negotiation with competition (with a call for competition), restricted procedure, transport equipment sector, and food sector can positively correlate with green contracts, or these factors increase the possibility of a contract being green. Explicit explanations on these relations are provided. This research identifies factors relating with and influencing the application of green award criteria in public contracts, which would inform public sectors on efficient resources allocation in terms of increasing green public procurement performance.
A Novel Method of Quantifying Catchment‐Wide Average Peak Propagation Speed in Hillslopes: Fast Hillslope Responses are Detected During Annual Floods in a Steep Humid Catchment

The lag time between rainfall input and discharge output—that is, the response speed of a catchment—is a key parameter for flood prediction but is difficult to quantify. Here we propose a new method to quantify catchment‐wide average peak propagation speed in hillslopes based on measurements conducted in a steep 4.5‐km2 catchment. The peak lag time of the catchment was partitioned into lag times in the hillslope and channel. Peak propagation speed was calculated from flow path length divided by lag time. We verified the results and evaluated the applicability and uncertainty of this method. This method can be applied during intense storms with identifiable peak relationships between rainfall and discharge. The effect of spatial variation in precipitation was insignificant in the study catchment. The increase in rainfall intensity and the rainfall accumulated prior to peak rainfall increased peak propagation speed. The method used to characterize flow path length from distributed values introduced some uncertainty. We calculated modal lengths using linear and logarithmic scales and various bin widths. These calculations resulted in small differences in modal channel length but led to more than tenfold differences in modal hillslope length. Thus, uncertainties for peak propagation speed across all hillslopes varied by one order of magnitude. Hillslope lag times were less than 2 min and peak propagation speed in the hillslopes ranged from 0.04 to 4.3 m/s for floods with recurrence intervals of one to several years. The proposed method and calculated data should improve prediction accuracy for extreme floods.
Economics of Procrastination: The Case of EU Grants

Purpose: This article concerns the study of economic effects of procrastination. The research sample consists of 6568 grant applications under EU programs in Poland, collated in order to establish whether the delay in submitting the application is a statistically significant factor affecting the quality of the application and the final financing decision. Design/methodology/approach: The study is based on three logistic regression models in which the dichotomous explained variable was a negative or a positive decision on the application. The most important explanatory variable for the study is the percentile of time in which the application is submitted - it represents the delay of the applicant. Findings: The result is confirmed by previous studies, which have proven that procrastination negatively affects organizations, and that the significant weight of undertaken projects can cause procrastination among leaders. Practical implications: As the study concerns European grants, determining the impact of procrastination on financing decisions can serve to better prepare potential beneficiaries for submitting an application, providing them with knowledge on whether an earlier submission translates into the probability of the application being successful or whether the persons managing the application process should better supervise their timely submission. Originality/value: To date, little research has been devoted to confirming the economic impact of procrastination. Previous studies mainly concern cost estimation caused by delaying employees, however, this study shows that procrastination has a real, significant impact on the economic efficiency of management activities. The methodology is innovative, because procrastination has not been previously analysed in terms of the time orientation of grant applications. Machine learning techniques have never been used in procrastination research. Moreover, the majority of research to date has focused primarily on individuals, on explaining what factors are statistically significantly related to procrastination or can lead to it through modelling, however, no research has been conducted to date in which statistical models would directly examine the economic impact of procrastination.