bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Changing Meanings of āśraya in Vasubandhu’s Abhidharmakośa(bhāṣya)
Authors: Szanyi Szilvia 
Published: September 2021

AbstractThe term āśraya (“support” or “basis”) is used in manifold ways in the Abhidharmakośa and its bhāṣya (AKBh). This comes from the fact that its basic meaning, indicating anything on which something else depends or rests, is quite generic. Despite the plasticity of its usage, we can find some recurring and distinct technical applications of the term in the AK(Bh), which I explore in my paper. First, I look at its usage of characterising a member of various asymmetric dependence relationships on which the arising and sometimes also the persistence of the other relatum depends. Through examining the nature of various āśraya-āśrita dependence relations the AK(Bh) discusses, I show that āśraya stands for an entity that determines the fundamental nature of the thing it supports. In the second half of the paper, I move on to those occurrences of the term where āśraya has a specific referent. While āśraya can refer to the six sense faculties (indriya) individually, it can also stand for them collectively pointing towards its widespread meaning as ‘psychophysical basis’. In this context, the focus often shifts either to the material or the mental elements that make up a sentient being. I will dedicate special attention to the discussion of the transformation of the basis (āśrayaparāvṛtti), where, on my reading, it is more natural to interpret āśraya as referring primarily to the mind (citta), with its bodily connotations being marginal.
Online Black-Markets: An Investigation of a Digital Infrastructure in the Dark
Authors: Spagnoletti Paolo , Ceci Federica , Bygstad Bendik 
Published: September 2021

AbstractThis paper investigates the functioning of Online Black-Markets (OBMs), i.e. a digital infrastructure operating in the Dark Net that enables the exchange of illegal goods such as drugs, weapons and fake digital identities. OBMs exist notwithstanding adverse conditions such as police interventions, scams and market breakdowns. Relying on a longitudinal case study, we focus on the dynamics of interactions among actors and marketplace technologies and we identify three mechanisms explaining OBMs operations. In particular, we show that OBMs infrastructure is the result of commoditization, platformization and resilience processes. Our contribution relies on the identification of community-based mechanisms that generate the OBMs infrastructure, extending the current understanding of e-commerce and social commerce.
General Education Teachers’ Perceptions of Autism, Inclusive Practices, and Relationship Building Strategies
Authors: Bolourian Yasamin , Losh Ainsley , Hamsho Narmene , Eisenhower Abbey , Blacher Jan 
Published: September 2021

AbstractTo identify target areas for professional development, this mixed-methods study examined general education teachers’ perceptions of autism and pedagogical practices in early elementary classrooms in the United States. In focus groups, teachers (N = 18) identified terms they associated with autism and strategies they used for inclusion and relationship building. Participants systematically free-listed and ranked their responses to three prompts. Using ranked responses, saliency scores were calculated to assess the perceived importance and frequency of responses. Teachers’ most salient perceptions of autism (e.g., social difficulties, focused/fixed interests) revealed an awareness of core symptoms. Salient inclusion practices included assigning special classroom responsibilities and showcasing student talents; salient relationship-building strategies included embracing students’ special interests and engaging in one-on-one time. Implications for teacher trainings are discussed.
How firms use coordination activities in university–industry collaboration: adjusting to or steering a research center?
Authors: Isaeva Irina , Steinmo Marianne , Rasmussen Einar 
Published: September 2021

AbstractUniversity–industry collaboration (UIC) is an important source of knowledge and innovation for firms but is often challenging due to the partners’ different goals. Thus, formal research centers have become a key policy instrument to foster stronger UIC whereby strong mutual relationships are created. This study investigates the establishment of a university–industry research center to gain insights into the coordination activities the focal firms used to achieve their goals with UIC. We find that the firms with goals related to specific innovations and technology development took a more active role by using structured coordination activities in the preformation phase of the research center, whereas the firms with goals related to general knowledge development mainly coordinated through unstructured activities when the center began operations. We map the specific coordination activities used in UIC and theorize on how the partners’ different organizational goals influenced their use of these activities. Our findings have important implications for how activities in UIC, particularly in research centers, can be designed to strengthen the collaboration between universities and their firm partners to enhance knowledge development and innovation.
Lender representatives on board of directors and internationalization in firms: an institutionalized agency perspective
Authors: Panicker Vidya Sukumara , Upadhyayula Rajesh Srinivas , Mitra Sumit 
Published: September 2021

AbstractFrom an agency perspective, the Anglo-Saxon features of corporate governance are predominantly explored by various studies in extant literature. However, it has recently been established that diverse and unique institutional configurations exist in different economies across the world and hence, the attitude of different actors within a firm, as shaped by institutional logics, can vary. Our study applies the institutionalized agency perspective to understand how the behaviour of different actors, within firms in the Indian institutional context, are shaped, consequently determining their roles in the strategic decisions of firms. We examine the representation of lenders in the board of directors, which is a characteristic of corporate governance in India. Our sample for this study consists of 985 unique Indian firms and 5513 firm year observations across the 2006–2017 time-period. We find a negative association between the proportion of lender representatives on board of directors and internationalization of firms. In addition, we also find that family ownership positively moderates this relation, whereas foreign institutional investors and domestic banks and financial institutional investors moderate this relationship negatively. In this manner, we explore the impact of institutional environment on a very specific actor (lenders) and their representatives towards internationalization.
Deep space optical communications (DSOC) downlink simulation with varying PPM order
Authors: Aboagye Emmanuel Domfeh , Chen Shun-Ping 
Published: September 2021

AbstractDuring the course of a typical deep space mission like the Mars Earth mission, there exist a wide range of operating points, due to the different changes in geometry that consequently cause different link budgets in terms of received signal and noise power. These changes include distance range, Sun-Earth-Probe angle, zenith angle and atmospheric conditions. The different operating points, with different losses (background noise, pointing losses and atmospheric losses), lead to different capacities and data rates over the course of a typical deep space mission. Consequently, different engineering parameters are adjusted and optimized to combat some of these varying losses in order to get acceptable data rates and bit error probabilities. This is a useful reason to analyze and simulate various operating conditions that occur with the varying spatial orbital time periods of the resulting received signal power level, noise power level, capacity, data rates and bit error probabilities. This paper details results of simulations of typical deep space optical communication link operation.
Maximum heat ratio: bi-directional method for fast and slow sap flow measurements
Authors: Lopez Jose Gutierrez , Pypker Thomas , Licata Julian , Burgess Stephen S. O. , Asbjornsen Heidi 
Published: September 2021

AbstractBackgroundAs sap flow research expands, new challenges such as fast sap flows or flows co-occurring with freeze/thaw cycles appear, which are not easily addressed with existing methods. In order to address these new challenges, sap flow methods capable of measuring bidirectional, high and slow sap flux densities (Fd, cm3cm−2 h−1), thermal properties and stem water content with minimum sensitivity to stem temperature are required.PurposeIn this study we assessed the performance of a new low-power ratio-based algorithm, the maximum heat ratio (MHR) method, and compare it with the widely known heat ratio (HR) method using a cut-tree study to test it under high flows usingEucalyptus grandistrees, and a freeze/thaw experiment usingAcer saccharumtrunks to test its response to fast changing stem temperatures that result in freeze/thaw cycles.ResultsOur results indicate that MHR and HR had a strong (R2 = 0.90) linear relationship within aFdrange of 0–45 cm3 cm−2 h−1. Using the MHR algorithm, we were able to estimate wood thermal properties and water content, while extending the measuring range of HR to approximately 0–130 (cm3cm−2 h−1). In our freeze/thaw experiment, the main discrepancy between MHR and HR was observed during freezing, where HR had consistently lowerFd(up to 10 cm3 cm−2 h−1), with respect to MHR. However, both algorithms identified similar zero flows.ConclusionConsequently, MHR can be an easy-to-implement alternative algorithm/method capable of handling extreme climatic conditions, which can also run simultaneously with HR.
Improving cold-start recommendations using item-based stereotypes
Authors: AlRossais Nourah , Kudenko Daniel , Yuan Tommy 
Published: September 2021

AbstractRecommender systems (RSs) have become key components driving the success of e-commerce and other platforms where revenue and customer satisfaction is dependent on the user’s ability to discover desirable items in large catalogues. As the number of users and items on a platform grows, the computational complexity and the sparsity problem constitute important challenges for any recommendation algorithm. In addition, the most widely studied filtering-based RSs, while effective in providing suggestions for established users and items, are known for their poor performance for the new user and new item (cold-start) problems. Stereotypical modelling of users and items is a promising approach to solving these problems. A stereotype represents an aggregation of the characteristics of the items or users which can be used to create general user or item classes. We propose a set of methodologies for the automatic generation of stereotypes to address the cold-start problem. The novelty of the proposed approach rests on the findings that stereotypes built independently of the user-to-item ratings improve both recommendation metrics and computational performance during cold-start phases. The resulting RS can be used with any machine learning algorithm as a solver, and the improved performance gains due to rate-agnostic stereotypes are orthogonal to the gains obtained using more sophisticated solvers. The paper describes how such item-based stereotypes can be evaluated via a series of statistical tests prior to being used for recommendation. The proposed approach improves recommendation quality under a variety of metrics and significantly reduces the dimension of the recommendation model.
Making the use of scenarios in LCA easier: the superstructure approach
Authors: Steubing Bernhard , de Koning Daniel 
Published: September 2021

Abstract
Purpose
Much progress has recently been made in modelling future background systems for LCA by including future scenario data, e.g. from Integrated Assessment Models (IAMs), into life cycle inventory (LCI) databases. A key problem is, however, that this yields potentially dozens of scenario LCI databases (i.e. LCI databases that represent different scenarios and reference years), instead of a single background database, which is very impractical for LCA modelling purposes. This paper proposes an approach to overcome this problem.

Methods
The approach consists of transforming all scenario LCI databases into a single superstructure database and an associated scenario difference file. The superstructure database is also a regular LCI database, but is constructed to contain all unique exchanges (elementary and intermediate flows) and processes that exist across all scenario LCI databases. The scenario difference file stores the differences between all scenarios and can be used to turn the superstructure into a specific scenario LCI database. This is very fast as it can be done in memory during LCA calculations.

Results and discussion
A key advantage of the superstructure approach is that a single LCI database can be used to represent different background systems. Therefore, the practitioner does not need to re-link a foreground system to multiple LCI databases, which is work-intensive and invites modelling errors. LCA results for all scenarios and reference years can be calculated automatically. We also illustrate how the superstructure approach has been implemented in the Activity Browser open source LCA software. Although this paper introduces the superstructure approach for background scenarios, it can also be used to model foreground scenarios, and even, as implemented in the Activity Browser, combinations of background and foreground scenarios. Finally, we briefly discuss further challenges that need to be addressed for a more widespread use of background scenarios in LCA.

Conclusions
The superstructure approach presents a practical solution for making the use of future background scenarios more wide-spread and, therefore, to overcome the problem of performing prospective LCA with temporally inconsistent foreground and background systems. The implementation in the Activity Browser makes the approach available for anyone and may serve as inspiration for other LCA software to implement the superstructure approach or a similar concept. While this may be an important technical milestone, additional coordination between data providers, scenario generators, LCA practitioners, and software developers will be required to further facilitate the use of background scenarios in prospective LCA studies.
Impact of Nonalcoholic Steatohepatitis on the Outcome of Patients Undergoing Roux-en-Y Gastric Bypass Surgery: a Propensity Score–Matched Analysis
Authors: Abbassi Ziad , Orci Lorenzo , Meyer Jeremy , Sgardello Sebastian Douglas , Goossens Nicolas , Rubbia-Brandt Laura , Spahr Laurent , Buchs Nicolas Christian , Mönig Stefan Paul , Toso Christian , Hagen Monika Elisabeth , Jung Minoa Karin 
Published: September 2021

Abstract
Purpose
It is currently unknown whether NASH (nonalcoholic steatohepatitis), as compared to simple steatosis, is associated with impaired postoperative weight loss and metabolic outcomes after RYGB surgery. To compare the effectiveness of Roux-en-Y gastric bypass (RYGB) on patients with NASH versus those with simple nonalcoholic fatty liver (NAFL).

Materials and Methods
We retrospectively retrieved data from 515 patients undergoing RYGB surgery with concomitant liver biopsy. Clinical follow-up and metabolic assessment were performed prior to surgery and 12 months after surgery. We used multivariate analysis of variance (MANOVA) and propensity score matching and we assessed for changes in markers of hepatocellular injury and metabolic outcomes.

Results
There were 421 patients with simple NAFL, and 94 with NASH. Baseline alanine and aspartate aminotransferases were significantly higher in patients with NASH (p < 0.01). Twelve months after the RYGB surgery, as determined by both MANOVA and propensity score matching, patients with NASH exhibited a significantly greater reduction in alanine aminotransferase (ß-coefficient − 12 iU/l [− 22 to − 1.83], 95% CI, adjusted p = 0.021) compared to their NAFL counterparts (31 matched patients in each group with no loss to follow-up at 12 months). Excess weight loss was similar in both groups (ß-coefficient 4.54% [− 3.12 to 12.21], 95% CI, adjusted p = 0.244). Change in BMI was comparable in both groups (− 14 (− 16.6 to − 12.5) versus − 14.3 (− 17.3 to − 11.9), p = 0.784).

Conclusion
After RYGB surgery, patients with NASH experience a greater reduction in markers for hepatocellular injury and similar weight loss compared to patients with simple steatosis.
Views on level $$\ell $$ curves, K3 surfaces and Fano threefolds
Authors: Garbagnati Alice , Verra Alessandro 
Published: September 2021

AbstractAn analogue of the Mukai map $$m_g: {\mathcal {P}}_g \rightarrow {\mathcal {M}}_g$$

m
g

:

P
g

→

M
g

is studied for the moduli $${\mathcal {R}}_{g, \ell }$$

R

g
,
ℓ

of genus g curves C with a level $$\ell $$
ℓ
structure. Let $${\mathcal {P}}^{\perp }_{g, \ell }$$

P

g
,
ℓ

⊥

be the moduli space of 4-tuples $$(S, {\mathcal {L}}, {\mathcal {E}}, C)$$

(
S
,
L
,
E
,
C
)

so that $$(S, {\mathcal {L}})$$

(
S
,
L
)

is a polarized K3 surface of genus g, $${\mathcal {E}}$$
E
is orthogonal to $${\mathcal {L}}$$
L
in $${{\,\mathrm{Pic}\,}}S$$

Pic

S

and defines a standard degree $$\ell $$
ℓ
K3 cyclic cover of S, $$C \in \vert {\mathcal {L}} \vert $$

C
∈
|
L
|

. We say that $$(S, {\mathcal {L}}, {\mathcal {E}})$$

(
S
,
L
,
E
)

is a level $$\ell $$
ℓ
K3 surface. These exist for $$\ell \le 8$$

ℓ
≤
8

and their families are known. We define a level $$\ell $$
ℓ
Mukai map $$r_{g, \ell }: {\mathcal {P}}^{\perp }_{g, \ell } \rightarrow {\mathcal {R}}_{g, \ell }$$

r

g
,
ℓ

:

P

g
,
ℓ

⊥

→

R

g
,
ℓ

, induced by the assignment of $$(S, {\mathcal {L}}, {\mathcal {E}}, C)$$

(
S
,
L
,
E
,
C
)

to $$ (C, {\mathcal {E}} \otimes {\mathcal {O}}_C)$$

(
C
,
E
⊗

O
C

)

. We investigate a curious possible analogy between $$m_g$$

m
g

and $$r_{g, \ell }$$

r

g
,
ℓ

, that is, the failure of the maximal rank of $$r_{g, \ell }$$

r

g
,
ℓ

for $$g = g_{\ell } \pm 1$$

g
=

g
ℓ

±
1

, where $$g_{\ell }$$

g
ℓ

is the value of g such that $$\dim {\mathcal {P}}^{\perp }_{g, \ell } = \dim {\mathcal {R}}_{g,\ell }$$

dim

P

g
,
ℓ

⊥

=
dim

R

g
,
ℓ

. This is proven here for $$\ell = 3$$

ℓ
=
3

. As a related open problem we discuss Fano threefolds whose hyperplane sections are level $$\ell $$
ℓ
K3 surfaces and their classification.
Modified chess patterns: handcrafted feature descriptors for facial expression recognition
Authors: Kartheek Mukku Nisanth , Prasad Munaga V. N. K. , Bhukya Raju 
Published: September 2021

AbstractFacial expressions are predominantly important in the social interaction as they convey the personal emotions of an individual. The main task in Facial Expression Recognition (FER) systems is to develop feature descriptors that could effectively classify the facial expressions into various categories. In this work, towards extracting distinctive features, Radial Cross Pattern (RCP), Chess Symmetric Pattern (CSP) and Radial Cross Symmetric Pattern (RCSP) feature descriptors have been proposed and are implemented in a 5 $$\times $$
×
5 overlapping neighborhood to overcome some of the limitations of the existing methods such as Chess Pattern (CP), Local Gradient Coding (LGC) and its variants. In a 5 $$\times $$
×
5 neighborhood, the 24 pixels surrounding the center pixel are arranged into two groups, namely Radial Cross Pattern (RCP), which extracts two feature values by comparing 16 pixels with the center pixel and Chess Symmetric Pattern (CSP) extracts one feature value from the remaining 8 pixels. The experiments are conducted using RCP and CSP independently and also with their fusion RCSP using different weights, on a variety of facial expression datasets to demonstrate the efficiency of the proposed methods. The results obtained from the experimental analysis demonstrate the efficiency of the proposed methods.
Model Order Reduction with Neural Networks: Application to Laminar and Turbulent Flows
Authors: Fukami Kai , Hasegawa Kazuto , Nakamura Taichi , Morimoto Masaki , Fukagata Koji 
Published: September 2021

AbstractWe investigate the capability of neural network-based model order reduction, i.e., autoencoder (AE), for fluid flows. As an example model, an AE which comprises of convolutional neural networks and multi-layer perceptrons is considered in this study. The AE model is assessed with four canonical fluid flows, namely: (1) two-dimensional cylinder wake, (2) its transient process, (3) NOAA sea surface temperature, and (4) a cross-sectional field of turbulent channel flow, in terms of a number of latent modes, the choice of nonlinear activation functions, and the number of weights contained in the AE model. We find that the AE models are sensitive to the choice of the aforementioned parameters depending on the target flows. Finally, we foresee the extensional applications and perspectives of machine learning based order reduction for numerical and experimental studies in the fluid dynamics community.
Gut Microbiome Alterations in COVID-19
Authors: Zuo Tao , Wu Xiaojian , Wen Weiping , Lan Ping 
Published: September 2021

Abstract
Since the outset of the coronavirus disease 2019 (COVID-19) pandemic, the gut microbiome in COVID-19 has garnered substantial interest, given its significant roles in human health and pathophysiology. Accumulating evidence is unveiling that the gut microbiome is broadly altered in COVID-19, including the bacterial microbiome, mycobiome, and virome. Overall, the gut microbial ecological network is significantly weakened and becomes sparse in patients with COVID-19, together with a decrease in gut microbiome diversity. Beyond the existence of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), the gut microbiome of patients with COVID-19 is also characterized by enrichment of opportunistic bacteria, fungi, and eukaryotic viruses, which are also associated with disease severity and presentation. Meanwhile, a multitude of symbiotic bacteria and bacteriophages are decreased in abundance in patients with COVID-19. Such gut microbiome features persist in a significant subset of patients with COVID-19 even after disease resolution, coinciding with ‘long COVID’ (also known as post-acute sequelae of COVID-19). The broadly-altered gut microbiome is largely a consequence of SARS-CoV-2infection and its downstream detrimental effects on the systemic host immunity and the gut milieu. The impaired host immunity and distorted gut microbial ecology, particularly loss of low-abundance beneficial bacteria and blooms of opportunistic fungi including Candida, may hinder the reassembly of the gut microbiome post COVID-19. Future investigation is necessary to fully understand the role of the gut microbiome in host immunity against SARS-CoV-2 infection, as well as the long-term effect of COVID-19 on the gut microbiome in relation to the host health after the pandemic.